The predictability of the logistic map is investigated for the joint impact of initial-condition (IC) and model uncertainty (bias + random variability) as well as simulation variability. To this end, Monte Carlo simulations are carried out where IC bias is varied in a wide range of 10⁻¹⁵–10⁻³, and, similarly, model bias is introduced in comparable range. It is found that while the predictability limit of the logistic map can be continuously extended by reducing IC bias, the introduction of the model bias imposes an upper limit to the predictability limit beyond which further reductions in IC bias do not lead to an extension in the predictability limit, effectively restricting the feasible joint space spanned by the IC-model biases. It is further observed that imposing a lower limit to the allowed variability among ensemble solutions (so as to prevent the ensemble variability from collapse) results in a similar constraint in the joint IC-model-bias space; but this correspondence breaks down when the imposed variability limit is too high (⁠ ∼>0.7 for the logistic map). Finally, although increasing the IC random variability in an ensemble is found to consistently extend the allowed predictability limit of the logistic map, the same is not observed for model parameter random variability. In contrast, while low levels of model parameter variability have no impact on the allowed predictability limit, there appears to be a threshold at which an abrupt transition occurs toward a distinctly lower predictability limit.

The Hurricane Weather Research and Forecasting (HWRF) model was the flagship hurricane model at NOAA’s National Centers for Environmental Prediction for 16 years and a state-of-the-art tool for tropical cyclone (TC) intensity prediction at the National Weather Service and across the globe. HWRF was a joint development between NOAA research and operations, specifically the Environmental Modeling Center and the Atlantic Oceanographic and Meteorological Laboratory. Significant support also came from the National Hurricane Center, Developmental Testbed Center, University Corporation for Atmospheric Research, universities, cooperative institutes, and the TC community. In the North Atlantic basin, where most improvement efforts focused, HWRF intensity forecast errors decreased by 45-50% at many lead times between 2007 and 2022. These large improvements resulted from increases in horizontal and vertical resolution, as well as advances in model physics and data assimilation. HWRF intensity forecasts performed particularly well over the Gulf of Mexico in recent years, providing useful guidance for a large number of impactful landfalling hurricanes. Such advances were made possible not only by significant gains in computing, but also through a substantial investment from the Hurricane Forecast Improvement Program.

Supercells in landfalling tropical cyclones (TCs) often produce tornadoes within 50 km of the coastline. The prevalence of TC tornadoes near the coast is not explained by the synoptic environments of the TC, suggesting a mesoscale influence is likely. Past case studies point to thermodynamic contrasts between ocean and land or convergence along the coast as a possible mechanism for enhancing supercell mesocyclones and storm intensity. This study augments past work by examining the changes in the hurricane boundary layer over land in the context of vertical wind shear. Using ground-based single- and dual-Doppler radar analyses, we show that the reduction in the boundary layer wind results in an increase in vertical wind shear/storm-relative helicity inland of the coast. We also show that convergence along the coast may be impactful to supercells as they cross the coastal boundary. Finally, we briefly document the changes in mesocyclone vertical vorticity to assess how the environmental changes may impact individual supercells.

Development of accurate planetary boundary layer (PBL) parameterizations in high-wind conditions is crucial for improving tropical cyclone (TC) forecasts. Given that Eddy-Diffusivity Mass-Flux (EDMF)-type PBL schemes are designed for non-hurricane boundary layers, this study examines the uncertainty of MF parameterizations in hurricane conditions by performing three-dimensional idealized simulations. Results show that the surface-driven MF plays a dominant role in the nonlocal turbulent fluxes and is comparable to the magnitude of downgradient momentum fluxes in the middle portion of TC boundary layers outside the radius of maximum wind (RMW); in contrast, the stratocumulus-top-driven MF is comparably negligible and exerts a marginal impact on TC simulations. To represent the impact of vertical wind shear on damping rising thermal plumes, a new approach of tapering surface-driven MF based on the surface stability parameter is proposed, aiming to retain the surface-driven MF only in unstable boundary layers. Compared to a traditional approach of MF tapering based on 10-m wind speeds, the new approach is physically more appealing as both shear and buoyancy forcings are considered and the width of the effective zone responds to diurnal variations of surface buoyancy forcing. Compared to the experiments retaining the original MF components, using either approach of MF tapering can lead to a stronger and more compact inner core due to enhanced boundary layer inflow outside the RMW; nevertheless, the radius of gale-force wind and inflow layer depth are only notably reduced using the new approach. Comparison to observations and further discussions on MF parameterizations in high-wind conditions are provided.

On September 30, 2021, a saildrone uncrewed surface vehicle intercepted Hurricane Sam in the northwestern tropical Atlantic and provided continuous observations near the eyewall. Measured surface ocean temperature unexpectedly increased during the first half of the storm. Saildrone current shear and upper-ocean structure from the nearest Argo profiles show an initial trapping of wind momentum by a strong halocline in the upper 30 m, followed by deeper mixing and entrainment of warmer subsurface water into the mixed layer. The ocean initial conditions provided to operational forecast models failed to capture the observed upper-ocean structure. The forecast models failed to simulate the warming and developed a surface cold bias of ~0.5°C by the time peak winds were observed, resulting in a 12-17% underestimation of surface enthalpy flux near the eyewall. Results imply that enhanced upper-ocean observations and, critically, improved assimilation into the hurricane forecast systems, could directly benefit hurricane intensity forecasts.

This study uses a recently-developed airborne Doppler radar database to explore how vortex misalignment is related to tropical cyclone (TC) precipitation structure and intensity change. It is found that for relatively weak TCs, defined here as storms with a peak 10-m wind of 65 kt or less, the magnitude of vortex tilt is closely linked to the rate of subsequent TC intensity change, especially over the next 12–36 h. In strong TCs, defined as storms with a peak 10-m wind greater than 65 kt, vortex tilt magnitude is only weakly correlated with TC intensity change. Based on these findings, this study focuses on how vortex tilt is related to TC precipitation structure and intensity change in weak TCs. To illustrate how the TC precipitation structure is related to the magnitude of vortex misalignment, weak TCs are divided into two groups: small-tilt and large-tilt TCs. In large-tilt TCs, storms display a relatively large radius of maximum wind, the precipitation structure is asymmetric, and convection occurs more frequently near the mid-tropospheric TC center than the lower-tropospheric TC center. Alternatively, small-tilt TCs exhibit a greater areal coverage of precipitation inward of a relatively small radius of maximum wind. Greater rates of TC intensification, including rapid intensification, are shown to occur preferentially for TCs with greater vertical alignment and storms in relatively favorable environments.

We utilized city-scale simulations to quantitatively compare the diverse urban overheating mitigation strategies, specifically tied to social vulnerability and their cooling efficacies during heatwaves. We enhanced the Weather Research and Forecasting model to encompass the urban tree effect and calculate Universal Thermal Climate Index for assessing thermal comfort. Taking Houston, Texas, U.S. as an example, the study reveals that equitably mitigating urban overheat is achievable by considering the city’s demographic composition and physical structure. Study results show that while urban trees may yield less cooling impact (0.27 K of Universal Thermal Climate Index in daytime) relative to cool roofs (0.30 K), the urban trees strategy can emerge as an effective approach for enhancing community resilience in heat stress-related outcomes. Social vulnerability-based heat mitigation was reviewed as Vulnerability-Weighted Daily Cumulative Heat Stress Change. Results underscore: (i) importance of considering the community resilience when evaluating heat mitigation impact, and (ii) the need to assess planting spaces for urban trees, rooftop areas, and neighborhood vulnerability when designing community-oriented urban overheating mitigation strategies.

Coupling a three-dimensional ocean circulation model to an atmospheric model can significantly improve forecasting of tropical cyclones (TCs). This is particularly true of forecasts for TC intensity (maximum sustained surface wind and minimum central pressure), but also for structure (e.g., surface wind-field sizes). This study seeks to explore the physical mechanisms by which a dynamic ocean influences TC evolution, using an operational TC model. The authors evaluated impacts of ocean-coupling on TC intensity and structure forecasts from NOAA’s Hurricane Analysis and Forecast System v1.0 B (HFSB), which became operational at the NOAA National Weather Service in 2023. The study compared existing HFSB coupled simulations with simulations using an identical model configuration in which the dynamic ocean coupling was replaced by a simple diurnally varying sea surface temperature model. The authors analyzed TCs of interest from the 2020–2022 Atlantic hurricane seasons, selecting forecast cycles with small coupled track-forecast errors for detailed analysis. The results show the link between the dynamic, coupled ocean response to TCs and coincident TC structural changes directly related to changing intensity and surface wind-field size. These results show the importance of coupling in forecasting slower-moving TCs and those with larger surface wind fields. However, there are unexpected instances where coupling impacts the near-TC atmospheric environment (e.g., mid-level moisture intrusion), ultimately affecting intensity forecasts. These results suggest that, even for more rapidly moving and smaller TCs, the influence of the ocean response to the wind field in the near-TC atmospheric environment is important for TC forecasting. The authors also examined cases where coupling degrades forecast performance. Statistical comparisons of coupled versus uncoupled HFSB further show an interesting tendency: high biases in peak surface winds for the uncoupled forecasts contrast with corresponding low biases, contrary to expectations, in coupled forecasts; the coupled forecasts also show a significant negative bias in the radii of 34 kt winds relative to National Hurricane Center best track estimates. By contrast, coupled forecasts show very small bias in minimum central pressure compared with a strong negative bias in uncoupled. Possible explanations for these discrepancies are discussed. The ultimate goal of this work will be to enable better evaluation and forecast improvement of TC models in future work.

Understanding how model physics impact tropical cyclone (TC) structure, motion, and evolution is critical for the development of TC forecast models. This study examines the impacts of microphysics and planetary boundary layer (PBL) physics on forecasts using the Hurricane Analysis and Forecast System (HAFS), which is newly operational in 2023. The “HAFS-B” version is specifically evaluated, and 3 sensitivity tests (for over 400 cases in 15 Atlantic TCs) are compared with retrospective HAFS-B runs. Sensitivity tests are generated by 1) Changing the microphysics in HAFS-B from Thompson to GFDL, 2) turning off the TC-specific PBL modifications that have been implemented in operational HAFS-B, and 3) combining the PBL and microphysics modifications. The forecasts are compared through standard verification metrics, and also examination of composite structure. Verification results show that Thompson microphysics slightly degrades the Day 3-4 forecast track in HAFS-B, but improves forecasts of long-term intensity. The TC-specific PBL changes lead to a reduction in a negative intensity bias and improvement in RI skill, but cause some degradation in prediction of 34-knot wind radii. Composites illustrate slightly deeper vortices in runs with the Thompson microphysics, and stronger PBL inflow with the TC-specific PBL modifications. These combined results demonstrate the critical role of model physics in regulating TC structure and intensity, and point to the need to continue to develop improvements to HAFS physics. The study also shows that the combination of both PBL and microphysics modifications (which are both included in one of the two versions of HAFS in the first operational implementation) leads to the best overall results.

An air-sea interaction field campaign was conducted in September of 2017 within the warm and cold eddy region of the western Northwest Pacific (WNP) (17.5°-20.5°N, 127.5°E-133.5°E). Both near-surface oceanic and atmospheric conditions in addition to ocean heat content (OHC) were examined to better understand the mechanisms governing high heat flux magnitudes responsible for rapidly intensifying tropical cyclones. Observations from this experiment indicate that the latent heat flux (LHF) under modest wind conditions reached 400 W m^-2 within the vicinity of a warm eddy, with OHC higher than 100 kJ cm^-2 of warm eddy region being 2-3 times as large as that of cold eddy region. These high OHC and a resultant high LHF in the warm eddy, comparable to the magnitude of LHF in the North Equatorial Current, may explain the mechanism of why tropical cyclones over a warm eddy in eddy-rich zones often rapidly intensify in the WNP. A month later typhoon Lan rapidly intensified into a super typhoon, while passing over the boundary region of warm and cold eddies during the observation period. Results from this study illustrate that both the wind-normalized LHF and the difference (Q_s-Q_a) between the specific humidity at air (Q_a) and at the sea surface (Q_s), closely correlate with OHC patterns, which suggests that the ocean looks likely to control the spatial pattern of LHF. Overall, both the ocean and weather conditions govern the pattern of specific humidity difference between the air-sea interface, with large OHC over the warm eddy controlling higher Q_s and the pattern of Q_a depending on the pattern of wind direction. Q_a as a factor impacting LHF magnitude is strongly linked to wind direction in the experimental area, that is, the drier northwesterly flow and southeasterly moist wind, resulting in the enhanced contrast of specific humidity at cold eddy region.

Super Typhoon Mangkhut, which traversed the North Equatorial Current (NEC; 8–17°N) in the western North Pacific in 2018, was the most intense Category-5 tropical cyclone (TC) with the longest duration in history—3.5 days. Here we show that the combination of two factors—high ocean heat content (OHC) and increased stratification — makes the NEC region the most favored area for a rapid intensification (RI) of super typhoons, instead of the Eddy Rich Zone (17–25°N), which was considered the most relevant for RI occurrence. The high OHC results from a northward deepening thermocline in geostrophic balance with the westward-flowing NEC. The stratification is derived from precipitation associated with the Inter-Tropical Convergence Zone in the summer peak typhoon season. These factors, which are increasingly significant over the past four decades, impede the TC-induced sea surface cooling, thus enhancing RI of TCs and simultaneously maintaining super typhoons over the NEC region.

:  The first operational version of the coupled Hurricane Analysis and Forecast System (HAFSv1) launched in 2023 consists of the HYbrid Coordinate Ocean Model (HYCOM) and finite-volume cubed-sphere (FV3) dynamic atmosphere model. This system is a product of efforts involving improvements and updates over a 4-year period (2019–2022) through extensive collaborations between the Environmental Modeling Center at the US National Centers for Environmental Prediction (NCEP) and NOAA Atlantic Oceanography and Meteorology Laboratory. To provide two sets of numerical guidance, the initial operational capability of HAFSv1 was configured to two systems—HFSA and HFSB. In this study, we present in-depth analysis of the forecast skills of the upper ocean that was co-evolved by the HFSA and HFSB. We chose hurricane Laura (2020) as an example to demonstrate the interactions between the storm and oceanic mesoscale features. Comparisons performed with the available in situ observations from gliders as well as Argos and National Data Buoy Center moorings show that the HYCOM simulations have better agreement for weak winds than high winds (greater than Category 2). The skill metrics indicate that the model sea-surface temperature (SST) and mixed layer depth (MLD) have a relatively low correlation. The SST, MLD, mixed layer temperature (MLT), and ocean heat content (OHC) are negatively biased. For high winds, SST and MLT are more negative, while MLD is closer to the observations with improvements of about 8%–19%. The OHC discrepancy is proportional to predicted wind intensity. Contrarily, the mixed layer salinity (MLS) uncertainties are smaller and positive for higher winds, probably owing to the higher MLD. The less-negative bias of MLD for high winds implies that the wind-force mixing is less effective owing to the higher MLD and high buoyancy stability (approx. 1.5–1.7 times) than the observations. The heat budget analysis suggests that the maximum heat loss by hurricane Laura was O(< 3°C per day). The main contributor here is advection, followed by entrainment, which act against or with each other depending on the storm quadrant. We also found relatively large unaccountable heat residuals for the in-storm period, and the residuals notably led the heat tendency, meaning that further improvements of the subscale simulations are warranted. In summary, HYCOM simulations showed no systematic differences forced by either HFSA or HFSB.

The water vapor transport associated with latent heat flux (LE) in the planetary boundary layer (PBL) is critical for the atmospheric hydrological cycle, radiation balance, and cloud formation. The spatiotemporal variability of LE and water vapor mixing ratio (r_v) are poorly understood due to the scale-dependent and nonlinear atmospheric transport responses to land surface heterogeneity. Here, airborne in situ measurements with the wavelet technique are utilized to investigate scale-dependent relationships among LE, vertical velocity (w) variance (σ²_w), and r_v variance (σ²_HO2) over a heterogeneous surface during the Chequamegon Heterogeneous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign. Our findings reveal distinct scale distributions of LE, σ²_w, and σ²_HO2 at 100 m height, with a majority scale range of 120 m–4 km in LE, 32 m–2 km in σ²_w, and 200 m–8 km in σ²_HO2. The scales are classified into three scale ranges, the turbulent scale (8–200 m), large-eddy scale (200 m–2 km), and mesoscale (2–8 km) to evaluate scale-resolved LE contributed by σ²_w and σ²_HO2. The large-eddy scale in PBL contributes over 70% of the monthly mean total LE with equal parts (50%) of contributions from σ²_w and σ²_HO2. The monthly temporal variations mainly come from the first two major contributing classified scales in LE, σ²_w, and  σ²_HO2. These results confirm the dominant role of the large-eddy scale in the PBL in the vertical moisture transport from the surface to the PBL, while the mesoscale is shown to contribute an additional ∼20%. This analysis complements published scale-dependent LE variations, which lack detailed scale-dependent vertical velocity and moisture information.

The distribution of tropical cyclone (TC) eye cloud heights is documented for the first time using compact Raman lidar (CRL) measurements with high spatial resolution. These cloud heights act as tracers for low-level vertical mixing in the eye region. Cloud height distributions using all available data from nine Atlantic TCs in 2021 and 2022 show significant vertical variance, dispelling the notion of a flat stratiform eye cloud deck. Eye cloud widths are multiscale, with shallow convective clouds dominating CRL returns. Data from Hurricane Sam (2021) highlight the evolution of shallow convective clouds in the TC eye and their associated temperature inversions. The frequent appearance of convective eye clouds, along with observed vertical wind fluctuations, suggests that vertical mixing from the boundary layer frequently occurs in the TC eye, even beneath strong inversions. This strong vertical mixing should be accurately portrayed by TC simulations and forecasts.

Tropical cyclone (TC) structure and intensity are strongly modulated by interactions with deep-layer vertical wind shear (VWS)—the vector difference between horizontal winds at 200 and 850 hPa. This paper presents a comprehensive review of more than a century of research on TC-VWS interactions. The literature broadly agrees that a TC vortex becomes vertically tilted, precipitation organizes into a wavenumber-one asymmetric pattern, and thermal and kinematic asymmetries emerge when a TC encounters an environmental sheared flow. However, these responses depend on other factors, including the magnitude and direction of horizontal winds at other vertical levels between 200 and 850 hPa, the amount and location of dry environmental air, and the underlying sea-surface temperature. While early studies investigated how VWS weakens TCs, an emerging line of research has focused on understanding how TCs intensify under moderate and strong VWS (i.e., shear magnitudes greater than 5 m s⁻¹). Modeling and observational studies have identified four pathways to intensification: vortex tilt reduction, vortex reformation, axisymmetrization of precipitation, and outflow blocking. These pathways may not be uniquely different because convection and vortex asymmetries are strongly coupled to each other. Besides discussing these topics, this review presents open questions and recommendations for future research on TC-VWS interactions.

The physical processes that govern eyewall replacement cycles (ERCs) in tropical cyclones (TCs) are not yet fully understood. In particular, asymmetric structures within the TC inner core have an uncertain role in ERC dynamics. This study analyzes the kinematic and precipitation asymmetric structures during successive ERCs in Hurricane Ivan (2004) using airborne Doppler radar observations. The azimuthal locations of these asymmetries are analyzed relative to the deep-layer (850-200 hPa) environmental wind shear vector. Two ERCs were analyzed at different stages of their evolution. During the concentric eyewall stage of the first ERC, the outer eyewall updrafts were strongest in the left-of-shear half, which also coincided with mesoscale descending inflow (MDI) just radially outward. Enhanced low-level convergence, updrafts, and MDI were collocated in an zone spiraling inward towards the strongest outer eyewall updrafts, suggesting that the vertical velocity asymmetry in the outer eyewall was possibly forced by a stratiform-induced cold pool similar to MDI impacts seen in past TC studies. During the final stage of the second ERC, the outer eyewall (now the singular primary eyewall) experienced an upwind shift in the precipitation and vertical velocity asymmetries. The updraft maximum shifted from the downshear-left quadrant to the downshear-right quadrant, and the precipitation maximum (downwind of the updraft maximum) shifted from left-of-shear to the downshear direction. This shift corroborates previous studies, which hypothesize that at the end of an ERC, the forcing mechanism that drives the eyewall vertical velocity asymmetry transitions from MDI/cold-pool processes to direct interaction with the environmental wind shear.

While recent observational studies of intensifying (IN) versus steady-state (SS) hurricanes have noted several differences in their axisymmetric and asymmetric structures, there remain gaps in the characterization of these differences in a fully three-dimensional framework. To address these limitations, this study investigates differences in the shear-relative asymmetric structure between IN and SS hurricanes using airborne Doppler radar data from a dataset covering an extended period of time. Statistics from individual cases show that IN cases are characterized by peak wavenumber-1 ascent concentrated in the upshear-left (USL) quadrant at ~12-km height, consistent with previous studies. Moderate updrafts (2–6 m s⁻¹) occur more frequently in the downshear eyewall for IN cases than for SS cases, likely leading to a higher frequency of moderate to strong updrafts USL above 9-km height. Composites of IN cases show that low-level outflow from the eye region associated with maximum wavenumber-1 vorticity inside the radius of maximum wind (RMW) in the downshear-left quadrant converges with low-level inflow outside the RMW, forming a stronger local secondary circulation in the downshear eyewall than SS cases. The vigorous eyewall convection of IN cases produces a net vertical mass flux increasing with height up to ~5-km and then is almost constant up to 10 km, whereas the net vertical mass flux of SS cases decreases with height above 4 km. Strong USL upper-level ascent provides greater potential for the vertical development of the hurricane vortex, which is argued to be favorable for continued intensification in shear environments.

This study describes both the research-to-operations process leading to a recent change in tropical cyclone (TC) reconnaissance sampling patterns, as well as observing-system experiments that evaluated the impact of that change on numerical weather prediction model forecasts of TCs. A valuable part of this effort was having close, multi-pronged connections between the TC research and operational TC prediction communities at the National Oceanic and Atmospheric Administration (NOAA). Related to this work, NOAA’s Atlantic Oceanographic and Meteorological Laboratory (AOML) and National Hurricane Center (NHC) have a long history of close collaboration to improve TC reconnaissance. Similar connections between AOML and NOAA’s Environmental Modeling Center (EMC) also laid a foundation for the observing-system experiments conducted here. More specifically, AOML and NHC collaborated in 2018 to change how NHC uses NOAA’s Gulfstream-IV (G-IV) jet during TC synoptic surveillance missions. That change added a second circumnavigation at approximately 1.5 degrees from TC centers, when possible. Preliminary experiments suggest that the change improved track forecasts, although intensity results were more mixed. Despite the somewhat small sample size over a three-year period, the track improvement does agree with prior work. This effort has led to additional work to more fully examine G-IV sampling strategies.

This study presents a method to diagnose radial ventilation, the horizontal flux of relatively low-θ_e air into tropical cyclones, from dropsonde observations. We used this method to investigate ventilation changes over three consecutive sampling periods in Hurricane Sam (2021), which underwent substantial intensity changes over three days. During the first and last periods, coinciding with intensification, the ventilation was relatively small due to a lack of spatial correlation between radial flow and θ_e azimuthal asymmetries. During the second period, coinciding with weakening, the ventilation was relatively large. The increased ventilation was caused by greater shear associated with an upper-level trough, tilting the vortex, along with dry, low-θ_e air wrapping in upshear. The spatial correlation of the radial inflow and anomalously low-θ_e air resulted in large ventilation at mid-to-upper levels. Additionally, at low-to-mid levels, there was evidence of mesoscale inflow of low-θ_e air in the stationary band complex. The location of these radial ventilation pathways and their effects on Sam’s intensity are consistent with previous idealized and real-case modeling studies. More generally, this method offers a way to monitor ventilation changes in tropical cyclones, particularly when there is full-troposphere sampling around and within a tropical cyclone’s core.

This study uses fixed buoy time series to create an algorithm for sea surface temperature (SST) cooling underneath a tropical cyclone (TC) inner-core. To build predictive equations, SST cooling is first related to single variable predictors such as the SST before storm arrival, ocean heat content (OHC), mixed layer depth, sea surface salinity and stratification, storm intensity, storm translation speed, and latitude. Of all the single variable predictors, initial SST before storm arrival explains the greatest amount of variance for the change in SST during storm passage. Using a combination of predictors, we created nonlinear predictive equations for SST cooling. In general, the best predictive equations have four predictors and are built with knowledge about the pre-storm ocean structure (e.g., OHC), storm intensity (e.g., minimum sea level pressure), initial SST values before storm arrival, and latitude. The best performing SST cooling equations are broken up into two ocean regimes: when the ocean heat content is less than 60 kJcm⁻² (greater spread in SST cooling values) and when the ocean heat content is greater than 60 kJcm⁻² (SST cooling is always less than 2 °C) which demonstrates the importance of initial oceanic thermal structure on the in-storm SST value. The new equations are compared to what is currently used in a statistical-dynamical model. Overall, since the ocean providing the latent heat and sensible heat fluxes necessary for TC intensification, the results highlight the importance for consistently obtaining accurate in-storm upper-oceanic thermal structure for accurate TC intensity forecasts.

This document summarizes the physics schemes used in two configurations of the first version of the operational Hurricane Analysis and Forecast System (HAFSv1) at NOAA NCEP. The physics package in HAFSv1 is the same as that used in NCEP global forecast system (GFS) version 16 except for an additional microphysics scheme and modifications to sea surface roughness lengths, boundary layer scheme, and the entrainment rate in the deep convection scheme. Those modifications are specifically designed for improving the simulation of tropical cyclones (TCs). The two configurations of HAFSv1 mainly differ in the adopted microphysics schemes and TC-specific modifications in addition to model initialization. Experiments are made to highlight the impacts of TC-specific modifications and different microphysics schemes on HAFSv1 performance. Challenges and developmental plans of physics schemes for future versions of operational HAFS are discussed.

The Typhoon Landfall Forecast Demonstration Project (TLFDP) (2010–2022) was an international cooperative scientific project conducted under the framework of the WMO. The primary objectives of the TLFDP were to enhance the capability of tropical cyclone (TC) forecasters, and support related decision-makers in effective utilization of the most advanced forecasting techniques for the ultimate purpose of reducing and preventing disasters associated with TC landfall. Forty agencies/organizations/projects globally participated in the activities of the TLFDP following its inception in 2010, although the primary focus was on landfalling TCs in the western North Pacific. The TLFDP facilitated collaborations and workshops that realized notable achievements in four key areas: 1) the collection, production, and sharing of TC data; 2) the development and application of TC forecast verification metrics; 3) research on TC forecast skill; and 4) development of new techniques for TC forecasting. An obvious outcome was the shift from prediction of TC features, including track and intensity, toward prediction of TC impacts with more probabilistic conception. The final years of the project also promoted increasing application of artificial intelligence and machine learning techniques in various techniques for analysis and forecasting of TCs. Although the TLFDP ended in 2022, its core activities have continued to be extended through new WMO projects and regional cooperative initiatives.

It is challenging to accurately characterize the three-dimensional distribution of horizontal wind vectors (known as 3D winds). Feature-matching satellite cloud top or water vapor fields have been used for decades to retrieve atmospheric motion vectors, but this approach is mostly limited to a single and uncertain pressure level at a given time. Satellite wind lidar measurements are expected to provide more accurate data and capture the line-of-sight wind for clear skies, within cirrus clouds, and above thick clouds, but only along a curtain parallel to the satellite track. Here we propose Vientos—a new satellite mission concept that combines two or more passive water vapor sounders with Doppler wind lidar to measure 3D winds. The need for 3D wind observations is highlighted by inconsistencies in reanalysis estimates, particularly under precipitating conditions. Recent studies have shown that 3D winds can be retrieved using water vapor observations from two polar-orbiting satellites separated by 50 min, with the help of advanced optical flow algorithms. These winds can be improved through the incorporation of a small number of collocated higher-accuracy measurements via machine learning. The Vientos concept would enable simultaneous measurements of 3D winds, temperature, and humidity, and is expected to have a significant impact on scientific research, weather prediction, and other applications. For example, it can help better understand and predict the preconditions for organized convection. This article summarizes recent results, presents the Vientos mission architecture, and discusses implementation scenarios for a 3D wind mission under current budget constraints.

The generation of ocean surface waves by wind has been studied for a century, giving rise to wave forecasting and other crucial applications. However, the reacting force of swell waves on the turbulence in the marine Atmospheric Boundary Layer (ABL) remains unknown partly due to the unclear magnitude and profile of Wave Coherent (WC) stress. In this study, the intersection frequency between the energy-containing range and inertial subrange range in the turbulent spectra is identified based on the Attached Eddy Model (AEM), as the intersection modulated by swell wave could help to comprehend the physical process between the ocean surface wave and the marine ABL. Using observations from a fixed platform located in the South China Sea, this study shows that the intersection when the WC stress accounts for a lower proportion of the total wind stress (< 10%) follows U/(2πz) given by AEM, here U is wind speed, z is height. While the intersection depends on the drag coefficient of WC stress for the case when WC stress accounts for a large part of the total wind stress (> 10%). Considering the unclear magnitude and profile of WC stress, this study derives a new function to depict the WC stress.

The Global Positioning System dropwindsonde has provided thousands of high-resolution kinematic and thermodynamic soundings in and around tropical cyclones (TCs) since 1997. These data have revolutionized the understanding of TC structure, improved forecasts, and validated observations from remote-sensing platforms. About 400 peer-reviewed studies on TCs using these data have been published to date. This paper reviews the history of dropwindsonde observations, changes to dropwindsonde technology since it was first used in TCs in 1982, and how the data have improved forecasting and changed our understanding of TCs.

This work reports a case study of the use of synthetic cyclone models for the development, assessment and validation of global navigation satellite system reflectometry (GNSS-R) wind speed remote sensing algorithms using a cyclone global navigation satellite system (CYGNSS) data record extending from 1 August 2018 to 31 December 2022. Synthetic cyclone models are shown to be useful in assessing the high wind speed sensitivity of CYGNSS’s v1.0, v2.1, v3.0, v3.1, and future v3.2 normalized bistatic radar cross Section (NBRCS) products due to the extended matchup dataset of high wind speed information that is obtained. The models are also shown useful in investigating the impacts of specific error corrections terms and in the development of level-2 geophysical model functions (GMFs) for the retrieval of ocean surface winds.

In this article, we show a “proof-of-concept” study to assess the utility of a variational quality control algorithm in increasing the number of assimilated Aeolus Mie-cloudy and Rayleigh-clear winds in National Oceanic and Atmospheric Administration (NOAA)'s global data assimilation and forecast system. The National Centers for Environmental Prediction (NCEP) Variational Quality Control (NCEP-VQC) algorithm was tuned and applied during the minimization process. This type of quality control uses optimal control theory principles to treat outliers in the probability density function (PDF) of observational departure statistics, assuming that the observation errors follow a family of logistic distributions. In the case of Aeolus Mie-cloudy and Rayleigh-clear winds, the NCEP-VQC algorithm permitted the relaxation of the gross error and one of the recommended ESA quality controls (reject Rayleigh-clear observations below 850 hPa), assigned adaptive observation weights ranging from 0 to 1, and led to an increase in the number of retained Aeolus observations for the calculation of global analyses, which in turn improved the verification statistics on analyzed tropical storms This article discusses the advantage of implementing the NCEP-VQC algorithm in the Aeolus data assimilation, the benefits of retaining more wind profiles that contribute to the analysis calculation, and shows improvements in the initialization and short-term forecasts on several tropical cyclone cases.

Continuous development and evaluation of planetary boundary layer (PBL) parameterizations in hurricane conditions are crucial for improving tropical cyclone (TC) forecasts. A turbulence kinetic energy (TKE)-based eddy-diffusivity mass-flux (EDMF-TKE) PBL scheme, implemented in NOAA’s Hurricane Analysis and Forecast System (HAFS), was recently improved in hurricane conditions using large-eddy simulations. This study evaluates the performance of HAFS TC forecasts with the original (experiment HAFA) and modified EDMF-TKE (experiment HAFY) based on a large sample of cases during the 2021 North Atlantic hurricane season. Results indicate that intensity and structure forecast skill was better overall in HAFY than in HAFA, including during rapid intensification. Composite analyses demonstrate that HAFY produces shallower and stronger boundary layer inflow, especially within 1–3 times the radius of maximum wind (RMW). Stronger inflow and more moisture in the boundary layer contribute to stronger moisture convergence near the RMW. These boundary layer characteristics are consistent with stronger, deeper, and more compact TC vortices in HAFY than in HAFA. Nevertheless, track skill in HAFY is slightly reduced, which is in part attributable to the cross-track error from a few early cycles of Hurricane Henri that exhibited ~400 n mi track error at longer lead times. Sensitivity experiments based on HAFY demonstrate that turning off cumulus schemes notably reduces the track errors of Henri while turning off the deep cumulus scheme reduces the intensity errors. This finding hints at the necessity of unifying the mass fluxes in PBL and cumulus schemes in future model physics development.

This contribution summarizes the significant progress in a variety of topic areas related to internal tropical cyclone (TC) intensity change processes over 2018–2022 from the WMO Tenth International Workshop on Tropical Cyclones (IWTC-10). These topic areas include surface and boundary layer processes; TC internal structure and microphysical processes; and, radiation interactions with TCs. Recent studies better frame the uncertainty in the surface drag and enthalpy coefficients at high wind speeds. These parameters greatly impact TC intensity and it is therefore important that more direct measurements of these boundary layer parameters are made. Particularly significant scientific strides have been made in TC boundary layers. These advancements have been achieved through improved coupled models, large-eddy simulations, theoretical advancements, and detailed observations. It is now clear that the research field needs to better represent the eddy viscosity throughout the depth of the boundary layer. Furthermore, detailed study of coherent structures in TC boundary layers will likely be a propitious direction for the research community. Meanwhile, in-depth observational field campaigns and assiduous data analysis have made significant headway into verifying theory and modeling studies of intensification processes related to TC vortex alignment, efficient latent heating distributions, and overall 3D structure. Substantial efforts have also been made to better understand the intricate roles radiative processes play in TC evolution and intensity change. Finally, some promising progress has been made in the development of time-dependent theories of TC intensification and the predictability of the internal TC intensity change. Overall, there have been well-earned gains in the understanding of intensity change processes intrinsic to the TC system, but the journey is not complete. This paper highlights some of the most relevant and important research areas that are still shedding new light into internal factors governing TC intensity change.

In this paper, we summarize findings from the Tenth International Workshop on Tropical Cyclones (IWTC-10) subgroup on operational track forecasting techniques and capability. The rate of improvement in the accuracy of official forecast tracks (OFTs) appears to be slowing down, at least for shorter lead times, where we may be approaching theoretical limits. Operational agencies continue to use consensus methods to produce the OFT with most continuing to rely on an unweighted consensus of four to nine NWP models. There continues to be limited use of weighted consensus techniques, which is likely a result of the skills and additional maintenance needed to support this approach. Improvements in the accuracy of ensemble mean tracks is leading to increased use of ensemble means in consensus tracks. Operational agencies are increasingly producing situation-dependent depictions of track uncertainty, rather than relying on a static depiction of track forecast certainty based on accuracy statistics from the preceding 5 years. This trend has been facilitated by the greater availability of ensemble NWP guidance, particularly vortex parameter files, and improved spread in ensembles. Despite improving spread-skill relationships, most ensemble NWP systems remain under spread. Hence many operational centers are looking to leverage "super-ensembles" (ensembles of ensembles) to ensure the full spread of location probability is captured. This is an important area of service development for multi-hazard impact-based warnings as it supports better decision making by emergency managers and the community in the face of uncertainty.

A Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) follow-on constellation, COSMIC-2, was successfully launched into equatorial orbit on June 24, 2019. With an increased signal-to-noise ratio due to improved receivers and digital beam-steering antennas, COSMIC-2 is producing about 5,000 high-quality radio-occultation (RO) profiles daily over the tropics and subtropics. The initial evaluation of the impact of assimilating COSMIC-2 into NOAA’s Global Forecast System (GFS) showed mixed results, and adjustments to quality control procedures and observation error characteristics had to be made prior to the assimilation of this dataset in the operational configuration in May 2020. Additional changes in the GFS that followed this initial operational implementation resulted in a larger percentage of rejection (~ 90 %) of all RO observations, including COSMIC-2, in the mid-lower troposphere. Since then, two software upgrades directly related to the assimilation of RO bending angle observations were developed. These improvements aimed at optimizing the utilization of COSMIC-2 and other RO observations to improve global weather analyses and forecasts. The first upgrade was implemented operationally in September 2021 and the second one in November 2022. This study describes both RO software upgrades and evaluates the impact of COSMIC-2 with this most recently improved configuration. Specifically, we show that the assimilation of COSMIC-2 observations has a significant impact in improving temperature and winds in the tropics, though benefits also extend to the extra-tropical latitudes.

Under very large vertical gradients of atmospheric refractivity, which are typical at the height of the planetary boundary layer, the assimilation of radio-occultation (RO) observations into numerical weather prediction (NWP) models presents several serious challenges. In such conditions, the assimilation of RO bending angle profiles is an ill-posed problem, the uncertainty associated with the RO observations is higher, and the one-dimensional forward operator used to assimilate these observations has several theoretical deficiencies. As a result, a larger percentage of these RO observations are rejected at the NWP centers by existing quality control procedures, potentially limiting the benefits of this data type to improve weather forecasting in the lower troposphere. To address these problems, a new methodology that enables the assimilation of RO data to be extended to the lower moist troposphere has been developed. Challenges associated with larger atmospheric gradients of refractivity are partially overcome by a reformulation that has minimal effect at higher altitudes. As a first step towards this effort, this study presents both the theoretical development of this new methodology and a forecast impact assessment of it using the NCEP NWP system. Though using a conservative approach, benefits in the lower tropical troposphere are already noticeable. The encouraging results of this work open the potential for further exploitation and optimization of RO assimilation.

As a tropical cyclone (TC) intensifies, the tangential wind field expands vertically and increases in magnitude. Observations and modeling support vortex height as an important TC structural characteristic. The Tropical Cyclone Radar Archive of Doppler Analyses with Recentering data set provides kinematic analyses for calculation of the height of the vortex (HOV) in observed storms. Analyses are azimuthally-averaged with tangential wind values taken along the radius of maximum winds. A threshold-based technique is used to determine the HOV. A fixed threshold HOV strongly correlates with current intensity. A dynamic HOV metric quantifies vertical decay of tangential wind with reduced dependency on intensity. Statistically significant differences are present between dynamic HOV values in groups of steady-state, intensifying, and rapidly-intensifying cases categorized by subsequent changes in pressure. A tall vortex is always observed in cases meeting a pressure-based rapid intensification definition. Taller vortices are also evident with slower intensification. Results suggest HOV may be a helpful predictor for TC intensification.

This study conducts the first large-sample comparison of the impact of dropsondes in the tropical cyclone (TC) inner core, vortex, and environment on NWP-model TC forecasts. We analyze six observing-system experiments, focusing on four sensitivity experiments that denied dropsonde observations within annuli corresponding with natural breakpoints in reconnaissance sampling. These are evaluated against two other experiments detailed in a recent parallel study: one that assimilated and another that denied dropsonde observations. Experiments used a basin-scale, multi-storm configuration of the Hurricane Weather Research and Forecasting model (HWRF) and covered active periods of the 2017–2020 North Atlantic hurricane seasons. Analysis focused on forecasts initialized with dropsondes that used mesoscale error covariance derived from a cycled HWRF ensemble, as these forecasts were where dropsondes had the greatest benefits in the parallel study. Some results generally support findings of previous research, while others are novel. Most notable was that removing dropsondes anywhere, particularly from the vortex, substantially degraded forecasts of maximum sustained winds. Removing in-vortex dropsondes also degraded outer-wind-radii forecasts in many instances. As such, in-vortex dropsondes contribute to a majority of the overall impacts of the dropsonde observing system. Additionally, track forecasts of weak TCs benefited more from environmental sampling, while track forecasts of strong TCs benefited more from in-vortex sampling. Finally, inner-core-only sampling strategies should be avoided, supporting a change made to the U.S. Air Force Reserve’s sampling strategy in 2018 that added dropsondes outside of the inner core.

This study marks the most comprehensive assessment of the overall impact of dropsondes on tropical cyclone (TC) forecasts to date. We compare two experiments to quantify dropsonde impact: one that assimilated and another that denied dropsonde observations. These experiments used a basin-scale, multi-storm configuration of the Hurricane Weather Research and Forecasting model (HWRF) and covered active North Atlantic basin periods during the 2017–2020 hurricane seasons. The importance of a sufficiently large sample size, as well as thoroughly understanding the error distribution by stratifying results, are highlighted by this work. Overall, dropsondes directly improved forecasts during sampled periods and indirectly impacted forecasts during unsampled periods. Benefits for forecasts of track, intensity, and outer wind radii were more pronounced during sampled periods. The forecast improvements of outer wind radii were most notable given the impact that TC size has on TC-hazards forecasts. Additionally, robustly observing the inner and near-core region was necessary for 64-kt-wind-radii forecasts. Yet, these benefits were heavily dependent on the data assimilation (DA) system quality. More specifically, dropsondes only improved forecasts when the analysis used mesoscale error covariance derived from a cycled HWRF ensemble, suggesting that it is a vital DA component. Further, while forecast improvements were found regardless of initial classification and in steady-state TCs, TCs undergoing intensity change had diminished benefits. The diminished benefits during intensity change probably reflects continued DA deficiencies. Thus, improving DA-system quality and observing system limitations would likely enhance dropsonde impacts.

This paper introduces a new tool for verifying tropical cyclone (TC) forecasts. Tropical cyclone forecasts made by operational centers and by numerical weather prediction (NWP) models have been objectively verified for decades. Typically, the mean absolute error (MAE) and/or MAE skill are calculated relative to values within the operations center’s best track. Yet, the MAE can be strongly influenced by outliers and yield misleading results. Thus, this paper introduces an assessment of consistency between the MAE skill as well as two other measures of forecast performance. This “consistency metric” objectively evaluates the forecast-error evolution as a function of lead time based on thresholds applied to the: (1) MAE skill; (2) median absolute error (MDAE) skill; and (3) the frequency of superior performance (FSP), which indicates how often one forecast outperforms another. The utility and applicability of the consistency metric is validated by applying it to four research and forecasting applications. Overall, this consistency metric is a helpful tool to guide analysis and increase confidence in results in a straightforward way. By augmenting the commonly-used MAE and MAE skill with this consistency metric and creating a single scorecard with consistency-metric results for TC track, intensity, and significant-wind radii forecasts, the impact of observing systems, new modeling systems, or model upgrades on TC-forecast performance can be evaluated both holistically and succinctly. This could in turn help forecasters learn from challenging cases and accelerate and optimize developments and upgrades in NWP models.

Prediction of the potentially devastating impact of landfalling tropical cyclones (TCs) relies substantially on numerical prediction systems. Due to the limited predictability of TCs and the need to express forecast confidence and possible scenarios, it is vital to exploit the benefits of dynamic ensemble forecasts in operational TC forecasts and warnings. RSMCs, TCWCs, and other forecast centers value probabilistic guidance for TCs, but the International Workshop on Tropical Cyclones (IWTC-9) found that the “pull-through” of probabilistic information to operational warnings using those forecasts is slow. IWTC-9 recommendations led to the formation of the WMO/WWRP Tropical Cyclone-Probabilistic Forecast Products (TC-PFP) project, which is also endorsed as a WMO Seamless GDPFS Pilot Project. The main goal of TC-PFP is to coordinate across forecast centers to help identify best practice guidance for probabilistic TC forecasts. TC-PFP is being implemented in 3 phases: Phase 1 (TC formation and position); Phase 2 (TC intensity and structure); and Phase 3 (TC related rainfall and storm surge). This article provides a summary of Phase 1 and reviews the current state of the science of probabilistic forecasting of TC formation and position. There is considerable variability in the nature and interpretation of forecast products based on ensemble information, making it challenging to transfer knowledge of best practices across forecast centers. Communication among forecast centers regarding the effectiveness of different approaches would be helpful for conveying best practices. Close collaboration with experts experienced in communicating complex probabilistic TC information and sharing of best practices between centers would help to ensure effective decisions can be made based on TC forecasts. Finally, forecast centers need timely access to ensemble information that has consistent, user-friendly ensemble information. Greater consistency across forecast centers in data accessibility, probabilistic forecast products, and warnings and their communication to users will produce more reliable information and support improved outcomes.

The multi-scale nature of tropical cyclone (TC) intensity change under moderate vertical wind shear was explored through an ensemble of high-resolution simulations of Hurricane Gonzalo (2014). Ensemble intensity forecasts were characterized by large short-term (36-h) uncertainty, with a forecast intensity spread of over 20 m s⁻¹, due to differences in the timing of rapid intensification (RI) onset. Two subsets of ensemble members were examined, referred to as early-RI and late-RI members. The two ensemble groups displayed significantly different vortex evolutions under the influence of a nearby upper-tropospheric trough and an associated dry-air intrusion. Mid-upper-tropospheric ventilation in late-RI members was linked to a disruption of inner-core diabatic heating, a more tilted vortex, and vortex breakdown, as the simulated TCs transitioned from a vorticity annulus toward a monopole structure. A column-integrated moist static energy (MSE) budget revealed the important role of horizontal advection in depleting MSE from the TC core, while mesoscale subsidence beneath the dry-air intrusion acted to dry a deep layer of the troposphere. Eventually, the dry-air intrusion retreated from late-RI members as vertical wind shear weakened, the magnitude of vortex tilt decreased, and late-RI members began to rapidly intensify, ultimately reaching a similar intensity as early-RI members. Conversely, the vortex structures of early-RI members were shown to exhibit greater intrinsic resilience to tilting from vertical wind shear and early-RI members were able to fend off the dry-air intrusion relatively unscathed. The different TC intensity evolutions can be traced back to differences in the initial TC vortex structure and intensity.

A synthesis of information products about environmental stressors provided in near real-time can serve environmental managers who seek to act decisively before stressors become unmanageable. We have created ecological forecasts, i.e., ecoforecasts, based on input from a variety of environmental sensors that report in near real-time, and we subsequently send those ecoforecasts to environmental managers. The application behind these ecoforecasts is Python-based software that uses an artificial intelligence (AI) inference engine called an expert system. The National Oceanic and Atmospheric Administration (NOAA) Environmental Information Synthesizer (NEIS), formerly the Environmental Information Synthesizer for Expert Systems (EISES), has been developed over two decades to meet the needs of environmental managers and scientists. NEIS integrates environmental data from multiple sources, including in situ and satellite sensors. The application produces ecoforecasts designed to identify environmental conditions conducive to mass coral bleaching and bleaching of specific coral species, as well as other marine environmental events such as algal blooms. This study evaluates the efficacy of coral bleaching ecoforecasts generated by NEIS for the Florida reef tract covering the years 2005–2017.

Hurricane Dorian (2019), a category-five tropical cyclone (TC), was characterized by a large spread in track forecasts as it moved northwest. A set of 80 ensemble forecasts from the Hurricane Analysis and Forecast System (HAFS) was produced to evaluate Dorian’s track spread and the factors that contributed to it. Track spread was particularly critical at long lead times (5–7 days after initialization near the Lesser Antilles), due to the uncertainty in the location of landfall and hazards. Four clusters of members were analyzed based on the 7-day track, characterized by Dorian moving: 1) slowly near the northern Bahamas (closest to reality), 2) across the Florida Peninsula, 3) slowly into Florida’s east coast, and 4) quickly north of The Bahamas. Ensemble sensitivity techniques were applied to identify areas that were most critical for Dorian’s track. Key differences were found in the strength of the subtropical ridge over the western Atlantic with a weaker ridge and slower easterly steering flow in the offshore groups. Subtle differences in the synoptic pattern over the United States also appeared to affect the timing of Dorian’s northward turn, specifically the strength of a shortwave trough moving over the Ohio Valley. Despite some early track differences, the correlation between early and late track errors was not significant. An examination of four members further highlights the differences in steering and the strength of the subtropical ridge. This study demonstrates the utility of ensemble datasets for studying TC forecast uncertainty, and the importance of medium-range modeling of synoptic-scale steering features to accurately predict the track of tropical cyclones.

During the 2022 hurricane season, real-time forecasts were conducted using an experimental version of the Hurricane Analysis and Forecast System (HAFS). The version of HAFS detailed in this paper (HAFSV0.3S, hereafter HAFS-S) featured the moving nest recently developed at NOAA AOML, and also model physics upgrades: TC-specific modifications to the planetary boundary layer (PBL) scheme and introduction of the Thompson microphysics scheme. The real-time forecasts covered a large dataset of cases across the North Atlantic and eastern North Pacific 2022 hurricane seasons, providing an opportunity to evaluate this version of HAFS ahead of planned operational implementation of a similar version in 2023. The track forecast results show that HAFS-S outperformed the 2022 version of the operational HWRF model in the Atlantic, and was the best of several regional hurricane models in the eastern North Pacific for track. The intensity results were more mixed, with a dropoff in skill at Days 4-5 in the Atlantic but increased skill in the eastern North Pacific. HAFS-S also showed some larger errors than the long-time operational Hurricane Weather Research and Forecasting (HWRF) model in the radius of 34-knot wind, but other radii metrics are improved. Detailed analysis of Hurricane Ian in the Atlantic highlights both the strengths of HAFS and opportunities for further development and improvement.

Observations of tropical cyclones (TC) from aircraft and in situ platforms provide critical and unique information for analyzing and forecasting TC intensity, structure, track, and their associated hazards. This report, prepared for the tenth International Workshop on Tropical Cyclones (IWTC-10), discusses the data collected around the world in TCs over the past four years since the IWTC-9, improvements to observing techniques, new instruments designed to achieve sustained and targeted atmospheric and oceanic observations, and select research results related to these observations. In the Atlantic and Eastern and Central Pacific basins, changes to operational aircraft reconnaissance are discussed along with several of the research field campaigns that have taken place recently. The changes in the use and impact of these aircraft observations in numerical weather prediction models are also provided along with updates on some of the experimental aircraft instrumentation. Highlights from three field campaigns in the Western Pacific basin are also discussed. Examples of in-situ data collected within recent TCs such as Hurricane Ian (2022), also demonstrate that new, emerging technologies and observation strategies reviewed in this report, definitely have the potential to further improve ocean-atmosphere coupled intensity forecasts.

At seasonal-to-interannual timescales, Atlantic hurricane activity is greatly modulated by El Niño–Southern Oscillation and the Atlantic Meridional Mode. However, those climate modes develop predominantly in boreal winter or spring and are weaker during the Atlantic hurricane season (June–November). The leading mode of tropical Atlantic sea surface temperature (SST) variability during the Atlantic hurricane season is Atlantic Niño/Niña, which is characterized by warm/cold SST anomalies in the eastern equatorial Atlantic. However, the linkage between Atlantic Niño/Niña and hurricane activity has not been examined. Here, we use observations to show that Atlantic Niño, by strengthening the Atlantic inter-tropical convergence zone rainband, enhances African easterly wave activity and low-level cyclonic vorticity across the deep tropical eastern North Atlantic. We show that such conditions increase the likelihood of powerful hurricanes developing in the deep tropics near the Cape Verde islands, elevating the risk of major hurricanes impacting the Caribbean islands and the U.S.

This study focused on developing a consensus machine learning (CML) model for tropical cyclone (TC) intensity-change forecasting, especially for rapid intensification (RI). This CML model was built upon selected classical machine learning models with the input data extracted from a high-resolution hurricane model, the Hurricane Weather Research and Forecasting (HWRF) system. The input data contained 21 or 34 RI-related predictors extracted from the 2018 version of HWRF (H218). This study found that TC inner-core predictors can be critical for improving RI predictions, especially the inner-core relative humidity. Moreover, this study emphasized that the importance of performing resampling on an imbalanced input dataset. Edited Nearest Neighbor and Synthetic Minority Oversampling Technique improved the Probability of Detection (POD) by ∼10% for the RI class. This paper also showed that the CML model has satisfactory performance on RI predictions compared to the operational models. CML reached 56% POD and 46% False Alarm Ratio (FAR), while the operational models had only 10 to 30% POD but 50 to 60% FAR. The CML performance on the non-RI classes was comparable to the operational models. The results indicated that, with proper and sufficient training data and RI-related predictors, CML has the potential to provide reliable probabilistic RI forecasts during a hurricane season.

Particle filters avoid parametric estimates for Bayesian posterior densities, which alleviates Gaussian assumptions in nonlinear regimes. These methods, however, are more sensitive to sampling errors than Gaussian-based techniques such as ensemble Kalman filters. A recent study by the authors introduced an iterative strategy for particle filters that match posterior moments–where iterations improve the filter’s ability to draw samples from non-Gaussian posterior densities. The iterations follow from a factorization of particle weights, providing a natural framework for combining particle filters with alternative filters to mitigate the impact of sampling errors. The current study introduces a novel approach to forming an adaptive hybrid data assimilation methodology, exploiting the theoretical strengths of non-parametric and parametric filters. At each data assimilation cycle, the iterative particle filter performs a sequence of updates while the prior sample distribution is non-Gaussian, then an ensemble Kalman filter provides the final adjustment when Gaussian distributions for marginal quantities are detected. The method employs the Shapiro-Wilk test to determine when to make the transition between filter algorithms, which has outstanding power for detecting departures from normality. Experiments using low-dimensional models demonstrate that the approach has significant value, especially for non-homogeneous observation networks and unknown model process errors. Moreover, hybrid factors are extended to consider marginals of more than one co-located variables using a test for multivariate normality. Findings from this study motivate the use of the proposed method for geophysical problems characterized by diverse observation networks and various dynamic instabilities, such as numerical weather prediction models.

The momentum roughness length (z₀) significantly impacts wind predictions in weather and climate models. Nevertheless, the impacts of z₀ parameterizations in different wind regimes and various model configurations on the hurricane size, intensity, and track simulations have not been thoroughly established. To bridge this knowledge gap, a comprehensive analysis of 310 simulations of 10 real hurricanes using the Weather Research and Forecasting (WRF) model is conducted in comparison with observations. Our results show that the default z₀ parameterizations in WRF perform well for weak (category 1-2) hurricanes; however, they underestimate the intensities of strong (category 3-5) hurricanes. This finding is independent of model resolution or boundary layer schemes. The default values of z₀ in WRF agree with the observational estimates from dropsonde data in weak hurricanes while they are much larger than observations in strong hurricanes regime. Decreasing z₀ close to the values of observational estimates and theoretical hurricane intensity models in high wind regimes (≳ 45 m s^-1) led to significant improvements in the intensity forecasts of strong hurricanes. A momentum budget analysis dynamically explained why the reduction of z₀ (decreased surface turbulent stresses) leads to stronger simulated storms.

Vertical eddy diffusivity (VED) in the planetary boundary layer (PBL) has a significant impact on forecasts of tropical cyclone (TC) structure and intensity. VED uncertainties in PBL parameterizations can be partly attributed to the model's inability to represent roll vortices (RV). In this study, RV effects on turbulent fluxes derived from a large eddy simulation (LES) by Li and Pu (2021) are added to the VED parameterization of the PBL scheme within the operational Hurricane Weather Research and Forecasting (HWRF) model. RV contribution to VED is parameterized through a coefficient and varies with the RV intensity and velocity scale. A modification over land has also been implemented. This modified VED parameterization is compared with the original wind-speed-dependent VED scheme in HWRF. Retrospective HWRF forecasts of Hurricanes Florence (2018) and Laura (2020) are analyzed to evaluate the impacts of the modified VED scheme on landfalling hurricane forecasts.Results show that the modified PBL scheme with the RV effect leads to an improvement in 10-m maximum wind speed forecasts of 14%-31%, with a neutral to positive improvement for track forecasts. Improved wind structure and precipitation forecasts against observations are also noted with the modified PBL scheme. Further diagnoses indicate that the revised PBL scheme enhances moist entropy in the boundary layer over land, leading to improved TC intensity prediction compared to the original scheme.

Hurricane Florence made landfall over the Carolinas 14 September 2018, bringing over 30 inches of rainfall. What remains understudied is the possible storm re-intensification by wet and warm antecedent soil moisture (ASM), known as the Brown Ocean Effect (BOE). This study investigates this effect with two approaches: (a) two satellite-based soil moisture (SM) data and (b) model simulation. The averaged Cyclone Global Navigation System and Soil Moisture Active Passive SM enables examination of land-atmosphere interaction at a sub-daily scale. Both observations and simulation results manifest positive feedback between ASM and rainfall intensity, with 3 days prior to landfall being the typical antecedent time scale. Wet (dry) ASM lead to intense (light) and concentrated (widespread) rains. We also found that soil temperature can modulate the BOE. This study aims to advance our understanding of land-atmosphere feedback and calls to acquire accurate antecedent land states to enhance forecast skills.

A storm tracking and nowcasting model was developed for the contiguous US (CONUS) by combining observations from the advanced baseline imager (ABI) and numerical weather prediction (NWP) short-range forecast data, along with the precipitation rate from CMORPH (the Climate Prediction Center morphing technique). A random forest-based model was adopted by using the maximum precipitation rate as the benchmark for convection intensity, with the location and time of storms optimized by using optical flow (OF) and continuous tracking. Comparative evaluations showed that the optimized models had higher accuracy for severe storms with areas equal to or larger than 5000 km² over smaller samples, and lower accuracy for cases smaller than 1000 km², while models with sample-balancing applied showed higher possibilities of detection (PODs). A typical convective event from August 2019 was presented to illustrate the application of the nowcasting model on local severe storm (LSS) identification and warnings in the pre-convection stage; the model successfully provided warnings with a lead time of 1–2 h before heavy rainfall. Importance score analysis showed that the overall impact from ABI observations was much higher than that from NWP, with the brightness temperature difference between 6.2 and 10.3 microns ranking at the top in terms of feature importance.

This study analyzes observations collected by multilevel towers to estimate turbulence parameters in the atmospheric surface layer of two landfalling tropical cyclones (TCs). The momentum flux, turbulent kinetic energy (TKE) and dissipation rate increase with the wind speed independent of surface types. However, the momentum flux and TKE are much larger over land than over the coastal ocean at a given wind speed range. The vertical eddy diffusivity is directly estimated using the momentum flux and strain rate, which more quickly increases with the wind speed over a rougher surface. Comparisons of the eddy diffusivity estimated using the direct flux method and that using the friction velocity and height show good agreement. On the other hand, the traditional TKE method overestimates the eddy diffusivity compared to the direct flux method. The scaling coefficients in the TKE method are derived for the two different surface types to better match with the vertical eddy diffusivity based on the direct flux method. Some guidance to improve vertical diffusion parameterizations for TC landfall forecasts in weather simulations are also provided.

Taking the examples of Hurricane Florence (2018) over the Carolinas and Hurricane Harvey (2017) over the Texas Gulf Coast, the study attempts to understand the performance of slab, single-layer Urban Canopy Model (UCM), and Building Environment Parameterization (BEP) in simulating hurricane rainfall using the Weather Research and Forecasting (WRF) model. The WRF model simulations showed that for an intense, large-scale event such as a hurricane, the model quantitative precipitation forecast over the urban domain was sensitive to the model urban physics. The spatial and temporal verification using the modified Kling-Gupta efficiency and Method for Object based Diagnostic and Evaluation in Time Domain suggests that UCM performance is superior to the BEP scheme. Additionally, using the BEP urban physics scheme over UCM for landfalling hurricane rainfall simulations has helped simulate heavy rainfall hotspots.

In this review, advances in the understanding of the controlling factors and physical mechanisms of tropical cyclogenesis (TCG) are summarized from recent (2018-2022) research on TCG, as presented in the Tenth International Workshop on Tropical Cyclones (IWTC-10). Observational, theoretical, and numerical modeling studies published in recent years have advanced our knowledge on the influence of large-scale environmental factors on TCG. Furthermore, studies have shown clearly that appropriate convective coupling with tropical equatorial waves enhances the development chances of TCG. More recently, illuminating research has been carried out on analyzing the mechanisms by which oscillations and teleconnections (El Niño Southern Oscillation (ENSO) in particular) modulate TCG globally, in association with changes in the sea surface temperature (SST). In addition to this, recent research has diligently addressed different aspects of TCG. Multiple studies have reported the applicability of unified theories and physical mechanisms of TCG in different ocean basins. Recently, research has been carried out on TCG under different flow pattern regimes, dry air intrusion, importance of marsupial pouch, genesis of Medicanes, wind shear, convection and vertical structure. Furthermore, studies have discussed the possibility of near equatorial TCG provided that there is enough supply of background vertical vorticity and relatively low vertical wind shear. Progress has been made to understand the role of climate change on global and regional TCG. However, there are still significant gaps which need to be addressed in order to better understand TCG prediction.

Airborne Doppler radar observations of the wind field in the tropical cyclone boundary layer (TCBL) during the landfall of Hurricane Ida (2021) are examined here. Asymmetries in tangential and radial flow are governed by tropical cyclone (TC) motion and vertical wind shear prior to landfall, while frictional effects dominate the asymmetry location during landfall. Strong TCBL inflow on the offshore-flow side of Ida occurs during landfall, while the location of the peak tangential wind at the top of the TCBL during this period is located on the onshore-flow side. A comparison of these observations with a numerical simulation of TC landfall shows many consistencies with the modeling study, though there are some notable differences that may be related to differences in the characteristics of the land surface between the simulation and the observations here.

The Tenth International Workshop on Tropical Cyclones (IWTC-10) occurred from 5-9 December 2022 in Bali, Indonesia. This workshop continued the goal of the original IWTC, held in 1985 in Bangkok, Thailand, to bring together forecasters and researchers from countries around the world that are impacted by tropical cyclones (TCs) to discuss the latest research and forecast advances and share best practices to improve TC forecasts globally. The workshops have continued as a regular feature of WMO efforts to encourage the advancement of TC forecasting and improve ways of communicating TC hazards to the general public. Global TC forecasting efforts in the past 10-15 years have emphasized hazards and impacts of landfalling TCs beyond just track and intensity. Additionally, there has been a growing interest in improving the communication of these hazards and impacts, using concepts from social and behavioral sciences, in ways that can lead to effective decision-making from stakeholders (e.g., government officials, emergency managers, media, general public). As such, the theme for IWTC-10 was “Improved TC science and services for better decision-making.” More about this theme, how the workshop was structured around it, and key outcomes from the workshop are discussed in this summary article.

This study presents an initial demonstration of assimilating small Uncrewed Aircraft System (sUAS) data into an operational model with a goal to ultimately improve tropical cyclone (TC) analyses and forecasts. The observations, obtained using the Coyote sUAS in Hurricane Maria (2017), were assimilated into the operational Hurricane Weather Research and Forecast system (HWRF) as they could be in operations. Results suggest that the Coyote data can benefit HWRF forecasts. A single-cycle case study produced the best results when the Coyote observations were assimilated at greater horizontal resolution with more relaxed quality control (QC) than comparable flight-level high-density observations currently used in operations. The case study results guided experiments that cycled HWRF for a roughly four-day period that covered all Coyote flights into Maria. The cycled experiment that assimilated the most data improved initial inner-core structure in the analyses and better agreed with other aircraft observations. The average errors in track and intensity decreased in the subsequent forecasts. Intensity forecasts were too weak when no Coyote data was assimilated, and assimilating the Coyote data made the forecasts stronger. Results also suggest that a symmetric distribution of Coyote data around the TC center is necessary to maximize its benefits in the current configuration of operational HWRF. Although the sample size was limited, these experiments provide insight for potential operational use of data from newer sUAS platforms in future TC applications.

Tropical cyclone (TC) precipitation poses serious hazards including freshwater flooding. High-resolution hurricane models predict the location and intensity of TC rainfall, which can influence local evacuation and preparedness policies. This study evaluates 0–72-hour precipitation forecasts from two experimental models, the Hurricane Analysis and Forecast System (HAFS) model and the Basin-scale Hurricane Weather Research and Forecasting (HWRF-B) model, for 2020 North Atlantic landfalling TCs. We use an object-based method that quantifies the shape and size of the forecast and observed precipitation. Precipitation objects are then compared for light, moderate, and heavy precipitation using spatial metrics (e.g., area, perimeter, elongation). Results show that both models forecast precipitation that is too connected, too close to the TC center, too enclosed around the TC center. Collectively, these spatial biases suggest that the model forecasts are too intense even though there is a negative intensity bias for both models, indicating there may be an inconsistency between the precipitation configuration and the maximum sustained winds in the model forecasts. The HAFS model struggles with forecasting stratiform versus convective precipitation and with the representation of lighter (stratiform) precipitation during the first six hours after initialization. No such spin-up issues are seen in the HWRF-B forecasts, which instead exhibit systematic biases at all lead times and systematic issues across all rain rate thresholds. Future work will investigate spin-up issues in the HAFS model forecast and how the microphysics parameterization affects the representation of precipitation in both models.

As a part of the Tropical Cyclone Rapid Intensification Project (TCRI), observations were made of the rapid intensification of Hurricane Sally (2020) as it passed over the Gulf ofMexico. High-altitude dropsondes and radar observations from NOAA’s Gulfstream IV, radar observations from WP-3D aircraft, the WSR-88D ground radar network, satellite images and satellite-detected lightning strikes are used to apply recently developed theoretical knowledge about tropical cyclone intensification. As observed in many other tropical cyclones, strong, bottom-heavy vertical mass flux profiles are correlated with low (but positive) values of low to mid-level moist convective instability along with high column relative humidity. Such mass flux profiles produce rapid spinup at low levels and the environmental conditions giving rise to them are associated with an intense mid-level vortex. This low-level spinup underneath the mid-level vortex results in the vertical alignment of the vortex column which is a key step in the rapid intensification process. In the case of Sally, the spinup of low-level vortex resulted from vorticity stretching, while the spinup of the mid-level vortex at 6 km resulted from vorticity tilting produced by the interaction of convective ascent with moderate vertical shear.

The distribution of turbulent kinetic energy (TKE) and its budget terms is estimated in simulated tropical cyclones (TCs) of various intensities. Each simulated TC is subject to storm motion, wind shear, and oceanic coupling. Different storm intensities are achieved through different ocean profiles in the model initialization. For each oceanic profile, the atmospheric simulations are performed with and without TKE advection. In all simulations, the TKE is maximized at low levels (i.e., below 1 km) and ∼0.5 km radially inward of the azimuthal-mean radius of maximum wind speed at 1-km height. As in a previous study, the axisymmetric TKE decreases with height in the eyewall, but more abruptly in simulations without TKE advection. The largest TKE budget terms are shear generation and dissipation, though variability in vertical turbulent transport and buoyancy production affect the change in the azimuthal-mean TKE distribution. The general relationships between the TKE budget terms are consistent across different radii, regardless of storm intensity. In terms of the asymmetric distribution in the eyewall, TKE is maximized in the front-left quadrant where the sea surface temperature (SST) is highest and is minimized in the rear-right quadrant where the SST is the lowest. In the category-5 simulation, the height of the TKE maximum varies significantly in the eyewall between quadrants and is between ∼400 m in the rear-right quadrant and ∼1,000 m in the front-left quadrant. When TKE advection is included in the simulations, the maximum eyewall TKE values are downwind compared to the simulations without TKE advection.

Over the past four years, significant research has advanced our understanding of how external factors influence tropical cyclone (TC) intensity changes. Research on air-sea interactions shows that increasing the moisture disequilibrium is a very effective way to increase surface heat fluxes and that ocean salinity-stratification plays a non-negligible part in TC intensity change. Vertical wind shear from the environment induces vortex misalignment, which controls the onset of significant TC intensification. Blocking due to upper-level outflow from TCs can reduce the magnitude of vertical wind shear, making for TC intensification. Enhanced TC-trough interactions are vital for rapid intensification in some TC cases because of strengthened warm air advection, but upper-level troughs are found to limit TC intensification in other cases due to dry midlevel air intrusions and increased shear. Aerosol effects on TCs can be divided into direct effects involving aerosol-radiation interactions and indirect effects involving aerosol-cloud interactions. The radiation absorption by the aerosols can change the temperature profile and affect outer rainbands through changes in stability and microphysics. Sea spray and sea salt aerosols are more important in the inner region, where the aerosols increase precipitation and latent heating, promoting more intensification. For landfalling TCs, the intensity decay is initially more sensitive to surface roughness than soil moisture, and the subsequent decay is mainly due to the rapid reduction in surface moisture fluxes. These new insights further sharpen our understanding of the mechanisms by which external factors influence TC intensity changes.

Airborne Doppler radar reflectivity data collected in hurricanes on the NOAA P-3 aircraft between 1997 and 2021 were parsed into different modes of precipitation: stratiform precipitation, shallow convection, moderate convection, and deep convection. Stratiform precipitation was the most frequent precipitation mode with 82.6% of all observed precipitation while deep convection was the most infrequent at 1.3%. When stratified by 12-hr intensity change, intensifying TCs had a greater areal coverage of total convection in the eyewall compared to weakening and steady-state TCs. The largest difference in the azimuthal distributions in the precipitation modes was in deep convection, which was mostly confined to the downshear-left quadrant in weakening and steady-state hurricanes and more symmetrically distributed in intensifying hurricanes. For all intensity change categories, the most symmetrically distributed precipitation mode was stratiform rain. To build upon the results of a recent thermodynamic study, the precipitation data were recategorized for hurricanes experiencing deep-layer wind shear with either a northerly-component or southerly-component. Like intensifying storms, hurricanes that experienced northerly-component shear had a more symmetric distribution of deep convection than southerly-component shear storms, which had a distribution of deep convection that resembled weakening storms. The greatest difference in the precipitation distributions between the shear direction groups were in major hurricanes experiencing moderate (4.5–11 m s⁻¹) wind shear values. Consistent with previous airborne radar studies, the results suggest that considering the distribution of deep convection and the thermodynamic distributions associated with differing environmental wind shear direction could aid TC intensity forecasts.

This paper summarizes the progress and activities of tropical cyclone (TC) operational forecast centers during the last four years (2018-2021). It is part II of the review on TC intensity change from the operational perspective in the rapporteur report presented to the 10th International Workshop on TCs (IWTC) held in Bali, Indonesia, from Dec. 5 - 9, 2022. Part I of the review has focused on the progress of dynamical model forecast guidance. This part discusses the performance of TC intensity and rapid intensification forecasts from several operational centers. It is shown that the TC intensity forecast errors have continued to decrease since the 9th IWTC held in 2018. In particular, the improvement of rapid intensification forecasts has accelerated, compared with years before 2018. Consensus models, operational procedures, tools and techniques, as well as recent challenging cases from 2018-2021 identified by operational forecast centers are described. Research needs and recommendations are also discussed.

This study examines the influence of radiative heating on the prediction of tropical cyclone (TC) intensification in the Hurricane Weather Research and Forecasting (HWRF) model. Previous idealized modeling and observational studies demonstrated that radiative heating can substantially modulate the evolution of TC intensity. However, the relevance of this process under realistic conditions remains unclear. Here, we use observed longwave radiative heating to explore the performance of TC forecasts in HWRF simulations. The performance of TC intensity forecasts is then investigated in the context of radiative heating forecasts. In observations and HWRF forecasts, high clouds near the TC center increase the convergence of radiative fluxes. A sharp spatial gradient (≥60 W/m²) in the flux convergence from the TC center outward toward the environment is associated with subsequent TC intensification. More accurate simulation of the spatial structure of longwave radiative heating is associated with more accurate TC intensity forecasts.

On 30 September 2021, a saildrone uncrewed surface vehicle (USV) was steered into Category 4 Hurricane Sam, the most intense storm of the 2021 Atlantic hurricane season. It measured significant wave heights up to 14 m (maximum wave height 27 m) and near-surface winds exceeding 55 m s⁻¹. This was the first time in more than seven decades of hurricane observations that in real time a USV transmitted scientific data, images, and videos of the dynamic ocean surface near a hurricane’s eyewall. The saildrone was part of a five-saildrone deployment of the NOAA 2021 Atlantic Hurricane Observations Mission. These saildrones observed the atmospheric and oceanic near-surface conditions of five other tropical storms, of which two became hurricanes. Such observations inside tropical cyclones help to advance the understanding and prediction of hurricanes, with the ultimate goal of saving lives and protecting property. The 2021 deployment pioneered a new practice of coordinating measurements by saildrones, underwater gliders, and airborne dropsondes to make simultaneous and near-collocated observations of the air-sea interface, the ocean immediately below, and the atmosphere immediately above. This experimental deployment opened the door to a new era of using remotely piloted uncrewed systems to observe one of the most extreme phenomena on Earth in a way previously impossible. This article provides an overview of this saildrone hurricane observations mission, describes how the saildrones were coordinated with other observing platforms, presents preliminary scientific results from these observations to demonstrate their potential utility and motivate further data analysis, and offers a vision of future hurricane observations using combined uncrewed platforms.

Extreme ocean events and severe weather systems have large environmental impacts but are under-observed due to their harsh conditions and associated challenges with deployments of in situ observing platforms. Through a public-private partnership, the NOAA Pacific Marine Environmental Laboratory (PMEL) has developed the saildrone uncrewed surface vehicle (USV) into a viable air-sea interaction observing platform that can be utilized by the broader ocean research community. PMEL and the NOAA Atlantic Oceanographic and Meteorological Laboratory have demonstrated the potential of USVs for observing the Arctic marginal ice zone during the seasonal Arctic ice retreat and for observing the extreme ocean and weather conditions inside major hurricanes. These USVs will be an essential part of the Global Ocean Observing System, providing real-time data to improve prediction of rapid climate change and extreme ocean and weather events and to reduce their harmful impacts.

This study investigates the relationship between the azimuthally averaged kinematic structure of the tropical cyclone boundary layer (TCBL) and storm intensity, intensity change, and vortex structure above the BL. These relationships are explored using composites of airborne Doppler radar vertical profiles, which have a higher vertical resolution than typically used three-dimensional analyses and therefore better capture TCBL structure. Results show that the BL height, defined by the depth of the inflow layer, is greater in weak storms than in strong storms. The inflow layer outside the radius of maximum tangential wind speed (RMW) is deeper in intensifying storms than in non-intensifying storms at an early stage. The peak BL convergence inside the RMW is larger in intensifying storms than in non-intensifying storms. Updrafts originating from the TCBL are concentrated near the RMW for intensifying TCs, while updrafts span a large radial range outside the RMW for non-intensifying TCs. In terms of vortex structure above the BL, storms with a quickly-decaying radial profile of tangential wind outside the RMW (“narrow” vortices) tend to have a deeper inflow layer outside the RMW, stronger inflow near the RMW, deeper and more concentrated strong updrafts close to the RMW, and weaker inflow in the outer core region than those with a slowly-decaying tangential wind profile (“broad” vortices). The narrow TCs also tend to intensify faster than broad TCs, suggesting that a key relationship exists among vortex shape, the BL kinematic structure, and TC intensity change. This relationship is further explored by comparisons of absolute angular momentum budget terms for each vortex shape.

The radially-outward propagating, cloud-top cooling, diurnal pulse (DP) is a prominent feature in tropical cyclones (TCs) that has important implications for changes in TC structure and intensity. By using an objective identification algorithm, this study characterizes DPs over various ocean basins and examines their environmental conditions and convective structures. DPs occur on 52% of TC days globally and the occurrence frequency exhibits significant regional variability. The Northwest Pacific (NWP) has the highest DP frequency (60%) and shares the largest fraction of DPs worldwide (34%).The median duration and propagation distance of DPs are 12–15 h and 500–600 km, respectively. Although the mean propagation speed of DPs is 11–13 m s^-1, persistent DPs (lasting >15 h) mostly propagate at speeds similar to internal inertial gravity waves (5–10 m s^-1). Additionally, the longer the pulse duration, the stronger the pulse amplitude. Further, most DPs initiate in the inner core overnight, in phase with inner-core deep convection. Inner-core cold clouds, precipitation, and lightning are all markedly enhanced on DP days compared to non-DP days. Interestingly, the DP signal significantly weakens and becomes slower while propagating through the 200–400-km annulus during 09–12 local time (LT). Finally, DPs are more likely to occur over warm sea surface temperatures (SSTs), in low shear, and with a moist mid- to upper-troposphere. SST plays an important role in DP development over all basins, while shear and humidity are less important in the NEP and NA basins.

This review summarizes the rapporteur report on tropical cyclone (TC) intensity change from the operational perspective, as presented to the 10th International Workshop on TCs (IWTC-10) held in Bali, Indonesia, from Dec. 5 - 9, 2022. The accuracy of TC intensity forecasts issued by operational forecast centers depends on three aspects: real-time observations, TC dynamical model forecast guidance, and techniques and methods used by forecasters. The rapporteur report covers the progress made over the past four years (2018-2021) in all three aspects. This review focuses on the progress of dynamical model forecast guidance. The companion paper (Part II) summarizes the advance from operational centers. The dynamical model forecast guidance continues to be the main factor leading to the improvement of operational TC intensity forecasts. Here, we describe recent advances and developments of major operational regional dynamical TC models and their intensity forecast performance, including HWRF, HMON, COAMPS-TC, Met Office Regional Model, CMA-TYM, and newly developed HAFS. The performance of global dynamical models, including NOAA's GFS, Met Office Global Model (MOGM), JMA's GSM, and IFS (ECMWF), has also been improved in recent years due to their increased horizontal and vertical resolution as well as improved data assimilation systems. Recent challenging cases of rapid intensification are presented and discussed.

Entrainment of dry moat air with low equivalent potential temperature laterally into the eyewall and rainbands is a unique turbulent process in the inner-core region of a tropical cyclone (TC). By analyzing in-situ aircraft measurements collected by the reconnaissance flights that penetrated the eyewalls and rainbands of Hurricanes Rita (2005), Patricia (2015), Harvey (2017), and Michael (2018), as well as numerical simulations of Hurricanes Patricia (2015), and Michael (2018), we show that the moat air entrained into the eyewall and rainbands meets the instability criterion, and therefore, sinks unstably as a convective downdraft. The resultant positive buoyancy fluxes are an important source for the turbulent kinetic energy (TKE) in the eyewall and rainband clouds. This mechanism of TKE generation via lateral entrainment instability should be included in the TKE-type turbulent mixing schemes for a better representation of turbulent transport processes in numerical forecasts of TCs.

Three-dimensional hurricane boundary layer (BL) structure is investigated during secondary eyewall formation, as portrayed in a high-resolution, full-physics simulation of Hurricane Earl (2010). This is the second part of a study on the evolution of BL structure during vortex decay. As in part 1 of this work, the BL’s azimuthal structure was linked to vertical wind shear and storm motion. Measures of shear magnitude and translational speed in Earl were comparable to Hurricane Irma (2017) in part 1, but the orientation of one vector relative to the other differed, which contributed to different structural evolutions between the two cases. Shear and storm motion influence the shape of low-level radial flow, which in turn influences patterns of spinup and spindown associated with the advection of absolute angular momentum M. Positive agradient forcing associated with the import of M in the inner core elicits dynamically restorative outflow near the BL top, which in this case was asymmetric and intense at times prior to eyewall replacement. These asymmetries associated with shear and storm motion provide an explanation for BL convergence and spinup at the BL top outside the radius of maximum wind (RMW), which affects inertial stability and agradient forcing outside the RMW in a feedback loop. The feedback process may have facilitated the development of a secondary wind maximum over approximately two days, which culminated in eyewall replacement.

A unique dataset obtained from the Coyote small uncrewed aircraft system (sUAS) in the inner-core boundary layer of Hurricane Maria (2017) is assimilated using NOAA’s Hurricane Ensemble Data Assimilation System (HEDAS) for data assimilation and Hurricane Weather Research and Forecast (HWRF) for model advances. The case of study is 1800 UTC 23 September 2017 when Maria was a Category-3 hurricane. In addition to the Coyote observations, measurements collected by the NOAA Lockheed WP-3D Orion and U.S. Air Force C-130 aircraft were also included. To support the assimilation of this unique dataset, a new online quality control (QC) technique in HEDAS scales the observation-background difference by the total uncertainty during data assimilation and uses the inter-quartile range outlier method to identify outlier observations. Experimental setup includes various very-frequent cycling scenarios for a Control that does not assimilate Coyote observations, assimilation of Coyote observations in addition to the Control observations, and the application of online QC. Findings suggest progressively improved analyses with more-frequent cycling, Coyote assimilation, and application of online QC. This applies to verification statistics computed at the locations of both Coyote and non-Coyote observations. In terms of the storm structure, only experiments that assimilated the Coyote observations were able to reproduce the double-eyewall structure that was observed at the time of the analysis, which is more consistent with the intensity of the storm according to the observations that were collected. Limitations of the study and future plans are also discussed.

To forecast tropical cyclone (TC) intensity and structure changes with fidelity, numerical weather prediction models must be “high definition”, i.e., horizontal grid spacing ≤ 3 km, so that they permit clouds and convection and resolve sharp gradients of momentum and moisture in the eyewall and rainbands. However, resolutions in operational global models remain too coarse to accurately predict these structures that are critical to TC intensity. Storm-following nests are a solution to this problem because they are computationally efficient at fine resolutions, providing a practical approach to improve TC intensity forecasts. Under the Hurricane Forecast Improvement Program, the operational Hurricane Weather Research and Forecasting (HWRF) system was developed to include telescopic, storm-following nests for a single TC per model integration. Subsequently, HWRF evolved into a state-of-the-art tool for TC predictions around the globe, although its single-storm nesting approach does not adequately simulate TC-TC interactions as they are observed. Basin-scale HWRF (HWRF-B) was developed later with a multi-storm nesting approach to improve the simulation of TC-TC interactions by producing high-resolution forecasts for multiple TCs simultaneously. In this study, the multi-storm nesting approach in HWRF-B was compared with a single-storm nesting approach using an otherwise identical model configuration. The multi-storm approach demonstrated TC intensity forecast improvements, including more realistic TC-TC interactions. Storm-following nests developed in HWRF and HWRF-B will be foundational to NOAA’s next-generation hurricane application in the Unified Forecast System. 

This study simulates five initially weak, moderately sheared tropical cyclones (TCs) from the 2020–2021 North Atlantic basin hurricane seasons using the Hurricane Analysis and Forecast System (HAFS). Four of the five simulations rapidly evolve from misaligned vortices with asymmetric precipitation and thermodynamic distributions toward more aligned and symmetric configurations. The displaced low-level (LLC) and mid-level circulations (MLC) non-monotonically progress toward alignment with periods of reformation, precession, and advection. Beginning 12–18 hr pre-alignment, TCs have increasingly greater mid-tropospheric humidity and areal coverages of precipitation downshear left than the simulation that fails to align. Alignment precedes the most sustained symmetrization of favorable thermodynamics and precipitation, but deep convection (not necessarily symmetric) plays a critical role in alignment. Ida (2021), a high impact US storm, undergoes a vortex-scale evolution where an increase in areal coverage and intensity of deep convection promotes a reformation of the vortex into a smaller compact core with a closed MLC (a closed LLC does not immediately form). This convective behavior downtilt helps to reshape the irrotational velocity field in the lower troposphere toward the reformed vortex. The increasingly convergent flow of favorable boundary layer thermodynamics within the inflow region thereby increases the instability, which maintains the persistent intense convection. The confluent flow ultimately promotes an advection of the pre-existing LLC toward the reformed vortex resulting in alignment. Tilt reductions are also shown to be temporally linked with the diurnal cycle, wherein convection preferentially increases near the center during the early morning hours (local time).

Dorian’s evolution from a weak, disorganized tropical storm to a rapidly intensifying hurricane is documented through a unique multi-platform synthesis of NOAA’s P-3 tail-Doppler radar, airborne in situ data, and Meteo-France’s Martinique and Guadeloupe ground radar network. Dorian initially struggled to intensify with a misaligned vortex in moderate mid-tropospheric vertical wind shear that also allowed detrimental impacts from dry air near the inner core. Despite vertical wind shear eventually decreasing to less than 5 m/s and an increasingly symmetric distribution of stratiform precipitation, the vortex maintained its misalignment with asymmetric convection for 12 hours. Then, as the low-level circulation (LLC) approached St. Lucia, deep convection near the LLC’s center dissipated, the LLC broadened, and precipitation expanded radially outwards from the center temporally coinciding with the diurnal cycle. Convection then developed farther downtilt within a more favorable, humid environment and deepened appreciably at least partially due to interaction with Martinique. A distinct repositioning of the LLC towards Martinique is induced by spin-up of a mesovortex into a small, compact LLC. It is hypothesized that this somewhat atypical reformation event and the repositioning of the vortex into a more favorable environment, farther from detrimental dry mid-tropospheric air, increased its favorability for the rapid intensification that subsequently ensued. Although the repositioning resulted in tilt reducing to less than the scale of the vortex itself, the pre-existing broad mid-upper level cyclonic envelope remained intact with continued misalignment observed between the mid-level center and repositioned LLC even during the early stages of rapid intensification.

Ten years of airborne Doppler radar observations are used to study convective updrafts' kinematic and reflectivity structures in tropical cyclone (TC) rainbands. An automated algorithm is developed to identify the strongest rainband updrafts across 12 hurricane-strength TCs. The selected updrafts are then collectively analyzed by their frequency, radius, azimuthal location (relative to the 200–850 hPa environmental wind shear), structural characteristics, and secondary circulation (radial/vertical) flow pattern. Rainband updrafts become deeper and stronger with increasing radius. A wavenumber-1 asymmetry arises, showing that in the downshear (upshear) quadrants of the TC, updrafts are more (less) frequent and deeper (shallower). In the downshear quadrants, updrafts primarily have in-up-out or in-up-in secondary circulation patterns. The in-up-out circulation is the most frequent pattern and has the deepest updraft and reflectivity tower. Upshear, the updrafts generally have out-up-in or in-up-in patterns. The radial flow of the updraft circulations largely follows the vortex-scale radial flow shear-induced asymmetry, being increased low-level inflow (outflow) and midlevel outflow (inflow) in the downshear (upshear) quadrants. It is hypothesized that the convective-scale circulations are significantly influenced by the vortex-scale radial flow at the updraft base and top altitudes. Other processes of the convective life cycle, such as bottom-up decay of aging convective updrafts due to increased low-level downdrafts, can influence the base altitude and, thus, the base radial flow of the updraft circulation. The findings presented in this study support previous literature regarding convective-scale patterns of organized rainband convection in a mature, sheared TC. 

The impact of low data latency is assessed using observations assimilated into the NCEP Finite-Volume Cubed-Sphere Global Forecast System (FV3GFS). Operationally, a full dataset is used to generate short-term (9-h) forecasts used as the background state for the next cycle, and a limited dataset with fewer observations is used for long-term (16-day) forecasts due to time constraints that exist in an operational setting. In this study, the sensitivity of the global weather forecast skill to the use of the full and limited data sets in both the short- and long-term forecasts (out to 10 days only) is evaluated. The results show that using the full dataset for long-term forecasts yields a slight improvement in forecast skill, while using the limited dataset for short-term forecasts yields a significant degradation. This degradation is primarily attributed to a decrease of in-situ observations rather than remotely-sensed observations, though no individual observation type captures the amount of degradation noted when all observations are limited. Furthermore, limiting individual types of in-situ observations (aircraft, marine, rawinsonde) does not result in the level of degradation noted when limiting all in-situ observations, demonstrating the importance of data redundancy in an operational observational system.

The behavior of drag coefficient (CD) in two different motion-relative quadrants of Typhoon Mujigae (2015) is investigated through the flux observations conducted on a fixed platform over the coastal region in the northern South China Sea. Observations reveal that the variation of CD is closely related to the location relative to the tropical cyclone (TC) center. The CD presents an enhancement when the typhoon is away from the observational site. The spatial distribution of CD on the periphery of a TC is asymmetric, and the CD in the right rear quadrant is much larger than that in the right front quadrant for the same wind speed range. This asymmetric distribution of CD can be explained by the differences in wave properties between the two quadrants. CD is smaller in cross-swell conditions than that in the along-wind wave conditions. Observations also confirm that CD tends to level off and even attenuate with the increase of wind speed, and the critical wind speed for CD saturation over the coastal region (∼20 m/s) is much lower than that over the open ocean (∼30 m/s). The observational spatial distribution of CD in TC quadrants not only improves our understanding on the air-sea momentum flux but also provides a potential solution for the long-standing scientific bottleneck on TC intensity forecasting.

Parameterizations of turbulent processes in planetary boundary layer (PBL) schemes impact tropical cyclone (TC) forecasts. Existing PBL schemes are mostly designed for low-wind conditions, and assessing their uncertainties in hurricane conditions remains challenging, mostly due to very scarce observations. Using a recently developed framework based on large-eddy simulations (LES), this study evaluates K-profile parameterization (KPP) and high-order PBL schemes in hurricane conditions. Among KPP PBL schemes, the Global Forecast System (GFS) scheme tends to produce excessively deep inflow layers with large values of eddy viscosity (K_m). Opposite results are found for the Yonsei University (YSU) scheme. Using LES results as a benchmark, the performance of YSU and GFS schemes is improved by modifying the “shape parameter” such that K_m is maximized closer to the surface, and by using a new definition of boundary layer height tailored to high-wind conditions. The LES results also suggest an asymptotic mixing length of ∼40 m can improve the Louis-type parameterizations of the YSU scheme that operates above the boundary layer. Among high-order PBL schemes, the Mellor–Yamada–Nakanishi–Niino (MYNN) scheme produces reasonably accurate vertical profiles of eddy viscosity, turbulent stress, and boundary layer winds under different high-wind conditions. Further analysis of MYNN supports a “three-layer” strategy for the mixing length parameterization for TCs that represents different types of turbulent regimes. In contrast, the high-order eddy-diffusivity mass-flux scheme produces excessive boundary-layer vertical mixing and a deeper inflow layer, partly attributable to a notable overestimation of the maximum allowable mixing length in the PBL code.

Accurately representing boundary layer turbulent processes in numerical models is critical to improve tropical cyclone forecasts. A new turbulence kinetic energy (TKE)-based moist eddy-diffusivity mass-flux (EDMF-TKE) planetary boundary layer scheme has been implemented in NOAA’s Hurricane Analysis and Forecast System (HAFS). This study evaluates EDMF-TKE in hurricane conditions based on a recently-developed framework using large-eddy simulation (LES). Single-column modeling tests indicate that EDMF-TKE produces much greater TKE values below 500-m height than LES benchmark runs in different high-wind conditions. To improve these results, two parameters in the TKE scheme were modified to ensure a match between the PBL and surface-layer parameterizations. Additional improvements were made by reducing the maximum allowable mixing length to 40 m based on LES and observations, by adopting a different definition of boundary layer height, and by reducing nonlocal mass fluxes in high-wind conditions. With these modifications, the profiles of TKE, eddy viscosity, and winds compare much better with LES results. Three-dimensional idealized simulations and an ensemble of HAFS forecasts of Hurricane Michael (2018) consistently show that the modified EDMF-TKE tends to produce a stronger vortex with a smaller radius of maximum wind than the original EDMF-TKE, while the radius of gale-force wind is unaffected. The modified EDMF-TKE code produces smaller eddy viscosity within the boundary layer compared to the original code, which contributes to stronger inflow, especially within the annulus of 1-3 times of radius of maximum wind. The modified EDMF-TKE shows promise to improve forecast skill of rapid intensification in sheared environments.

In this review, data assimilation (DA) techniques used for tropical cyclones (TCs) are briefly overviewed. The strength and weakness of variational methods, ensemble methods, hybrid methods, and particle filter methods are also discussed. Several global numerical weather prediction models and their corresponding DA systems frequently used for TC forecasting and verification are described first. The DA research and development efforts in the operational regional model from the National Centers for Environmental Prediction's Hurricane Weather Research and Forecasting are then discussed in greater detail. Focused remarks on TC observations from reconnaissance, ground-based radar, enhanced satellite-derived atmospheric motion vectors and all-sky satellite radiances and their impacts on TC analyses and forecasts are addressed. Recent TC DA advancements and challenges on better use of observations and more advanced DA methods for TC application are also briefly reviewed.

The National Hurricane Center (NHC) uses a variety of guidance models for its operational tropical cyclone track, intensity, and wind structure forecasts and as baselines for the evaluation of forecast skill. A set of the simpler models, collectively known as the NHC guidance suite, is maintained by NHC. The models comprising the guidance suite are briefly described and evaluated, with details provided for those that have not been documented previously. Decay-SHIFOR is a modified version of the Statistical Hurricane Intensity FORecast (SHIFOR) model that includes decay over land; this modification improves the SHIFOR forecasts through about 96 h. T-CLIPER, a climatology and persistence model that predicts track and intensity using a trajectory approach, has error characteristics similar to those of CLIPER track and D-SHIFOR but can be run to any forecast length. The Trajectory and Beta model (TAB), another trajectory track model, applies a grid-point spatial filter to smooth winds from the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS) model. TAB model errors were 10%-15% lower than those of the Beta and Advection model (BAM), the model it replaced in 2017. Optimizing TAB’s vertical weights shows that the lower troposphere’s environmental flow provides a better match to observed tropical cyclone motion than does the upper troposphere and that the optimal steering layer is shallower for higher-latitude and weaker tropical cyclones. The advantages and disadvantages of the D-SHIFOR, T-CLIPER and TAB models relative to their earlier counterparts are discussed.

For the last 7 years, Florida’s Coral Reef (FCR) has suffered from widespread and severe coral loss caused by stony coral tissue loss disease (SCTLD). First observed off the coast of Miami-Dade County in 2014, the outbreak has since spread throughout the entirety of FCR and some areas of the Caribbean. However, the propagation of the disease through FCR seemed to slow down when it reached the western end of the Marquesas in August 2020. Despite being present about 30 km (∼20 miles) from the Dry Tortugas (DRTO), SCTLD was not reported in this area before May 2021. As SCTLD transmission is likely to be waterborne, here we suggest that this apparently delayed propagation is related to eddy activity near the DRTO under the influence of the Loop Current/Florida Current system. To quantify the impact of the local ocean circulation on the spread of SCTLD from the Marquesas and the DRTO, we evaluated the hydrodynamic-predicted connectivity between these two regions using a high-resolution hydro-epidemiological model between May 2018 and May 2021. Our results suggest that the Marquesas and the DRTO were not connected during February-October 2020 and January-May 2021. These periods coincided with either the occurrence of Tortugas gyres and mean circulation with an eastward component between the Marquesas and the DRTO or the presence of southward currents. Our results suggest that disease agents probably reached the DRTO in November 2020 and that they most likely originated from southern or northwestern reefs of the Marquesas. This study provides novel insight into the role played by the hydrodynamics in the spread of SCTLD within the western-most edge of FCR, and in propagating the disease to uninfected locations

Tropical cyclones can form over open ocean where in situ observations are limited, so forecasters rely on satellite observations to monitor their development and track. We explore the utility of an operational satellite sounding product for tropical forecasting by characterizing the products retrieval skill during research flights. Scientists from both the NOAA-Unique Combined Atmospheric Processing System (NUCAPS) research team and tropical cyclone communities collaborated to target relevant tropical cyclones during the campaign. This effort produced 130 dropsondes that are well-timed with satellite sounder overpasses over three different tropical cyclones and one Saharan Air Layer outbreak. For the combined infrared and microwave retrieval, the NUCAPS temperature has a root mean square error (RMSE) of 1.2 K near the surface (1000–600 mb) and 0.8 K in the mid-troposphere (600–300 mb), which is in line with global product requirements. The water vapor mixing ratio RMSE was 26% near the surface and 46% in the mid-troposphere. NUCAPS microwave-only retrievals can also be useful for cloudy scenes, with surface RMSE values of 4 K (temperature) and 23% (water vapor). Using information content analysis, we estimated that the vertical resolution near the surface was 1.7 km for the temperature retrievals and 2.2 km for the water vapor retrievals in this study. We discuss the feasibility of implementing NUCAPS in an operational forecasting setting, which requires rapid data delivery to forecaster software tools.

This analysis introduces a novel airborne Doppler radar database, referred to as the Tropical Cyclone Radar Archive of Doppler Analyses with Recentering (TC-RADAR). TC-RADAR is comprised of over 900 analyses from 273 flights into TCs in the North Atlantic, eastern North Pacific, and central North Pacific basins between 1997–2020. This database contains abundant sampling across a wide range of TC intensities, which facilitated a comprehensive observational analysis on how the three-dimensional, kinematic TC inner-core structure is related to TC intensity. To examine the storm-relative TC structure, we implemented a novel TC center-finding algorithm. Here, we show that TCs below hurricane intensity tend to have monopolar radial profiles of vorticity and a wide range of vortex tilt magnitudes. As TC intensity increases, vorticity becomes maximized within an annulus inward of the peak wind, the vortex decays more slowly with height, and the vortex tends to be more aligned in the vertical. The TC secondary circulation is also strongly linked to TC intensity, as more intense storms have shallower and stronger lower-tropospheric inflow as well as larger azimuthally-averaged ascent. The distribution of vertical velocity is found to vary with TC intensity, height, and radial domain. These results—and the capabilities of TC-RADAR—motivate multiple avenues for future work, which are discussed. 

This study demonstrates a link between coastal downwelling and tropical cyclone (TC) intensification. We show that coastal downwelling increases air-sea enthalpy (heat, moisture) fluxes ahead of TCs as they approach land, creating conditions conducive to intensification even in the presence of typically inhibiting factors like strong vertical wind shear. The study uses a coupled TC model (HWRF-B) and buoy observations to demonstrate that coastal downwelling developed as three TCs in 2020 approached land. Results show downwelling maintained warmer sea-surface temperatures over the ocean shelf, enhancing air-sea temperature/humidity contrasts. We found that in such cases resulting air-sea enthalpy fluxes can replenish the boundary-layer even when cool, dry air intrudes, as in sheared storms and storms approaching continental land-masses. The resulting warm, moist air is advected into the TC inner core, enhancing convective development, thus providing energy for TC intensification. These results indicate coastal downwelling can be important in forecasting TC intensity change before landfall.

Better representation of the planetary boundary layer (PBL) in numerical models is one of the keys to improving forecasts of TC structure and intensity, including rapid intensification. To meet this goal, our recent work has used observations to improve the eddy-diffusivity mass flux with prognostic turbulent kinetic energy (EDMF-TKE) PBL scheme in the Hurricane Analysis and Forecast System (HAFS). This study builds on that work by comparing a modified version of EDMF-TKE (MEDMF-TKE) with the hybrid EDMF scheme based on a K-profile method (HEDMF-KP) in the 2020 HAFS-globalnest model. Verification statistics based on 101 cases in the 2020 season demonstrate that MEDMF-TKE improves track forecasts, with a reduction in a large right bias seen in HEDMF-KP forecasts. The comparison of intensity performance is mixed, but the magnitude of low bias at early forecast hours is reduced with the use of the MEDMF-TKE scheme, which produces a wider range of TC intensities. Wind radii forecasts, particularly the radius of maximum wind speed (RMW), are also improved with the MEDMF-TKE scheme. Composites of TC inner-core structure in and above the PBL highlight and explain differences between the two sets of forecasts, with MEDMF-TKE having a stronger and shallower inflow layer, stronger eyewall vertical velocity, and more moisture in the eyewall region. A case study of Hurricane Laura shows that MEDMF-TKE better represented the subtropical ridge and thus the motion of the TC. Finally, analysis of Hurricane Delta through a tangential wind budget highlights how and why MEDMF-TKE leads to faster spinup of the vortex and a better prediction of rapid intensification.

The global-nested Hurricane Analysis and Forecast System (HAFS-globalnest) is one piece of NOAA’s Unified Forecast System (UFS) application for hurricanes. In this study, results are analyzed from 2020 real-time forecasts by HAFS-globalnest and a similar global-nested model, the Tropical Atlantic version of GFDL’s System for High-resolution prediction on Earth- to- Local Domains (T-SHiELD). HAFS-globalnest produced the highest track forecast skill compared to several operational and experimental models, while T-SHiELD showed promising track skill as well. The intensity forecasts from HAFS-globalnest generally had a positive bias at longer lead times primarily due to the lack of ocean coupling, while T-SHiELD had a much smaller intensity bias particularly at longer forecast lead times. With the introduction of a modified planetary boundary layer scheme and an increased number of vertical levels, particularly in the boundary layer, HAFS forecasts of storm size had a smaller positive bias than occurred in the 2019 version of HAFS-globalnest. Despite track forecasts that were comparable to the operational GFS and HWRF, both HAFS-globalnest and T-SHiELD suffered from a persistent right-of-track bias in several cases at the 4-5 day forecast lead times. The reasons for this bias were related to the strength of the subtropical ridge over the western North Atlantic and are continuing to be investigated and diagnosed. A few key case studies from this very active hurricane season, including Hurricanes Laura and Delta, were examined. 

Dropsondes are small meteorological devices similar to radiosondes, which are launched from aircraft or long duration balloons. These instruments are typically deployed over oceans to target special meteorological conditions or satellite overpass areas. Dropsondes provide high-resolution profiles of pressure, temperature, relative humidity, and winds from the aircraft altitude down to the ocean surface. The technology behind these measurements includes the aircraft infrastructure to launch the sondes and to receive the data by telemetry. Observations by dropsondes provide reference measurements for retrievals from satellites and support the validation and calibration of temperature, humidity, surface winds, and wind profiles. Dropsondes also measure the integrated water vapor column, which indirectly supports the validation of cloud parameters. Dropsondes may also be used in the calibration and validation of airborne remote sensors, which may act as transfer standards and which can provide more data than would be possible from dropsondes. In addition, dropsondes are heavily used in characterizing the atmospheric state and spatial variability, in particular in severe weather events, which may also challenge space-borne sensors.

Weather forecasts are the foundation of much of the information needed in the warnings we have been considering. To be useful, they require knowledge of the current atmospheric state as a starting point. In this chapter, we first look at the methods used to predict the weather and the resulting demands for observations. Then, we explore the wide variety of sensors and platforms used to obtain this information. There has been a long history of close working between sensor and platform designers and meteorologists that has produced spectacular advances in forecast accuracy. However, the latest high-resolution models require new approaches to obtaining observations that will require different collaborations. Examples are presented of partnerships in space observing and in aviation, a demonstration system from Canada, and the use of testbeds and observatories as environments for progress

Raindrop size distributions collected by the DROPLET MEASUREMENT TECHNOLogies Precipitation imaging probe from 17 flights through 6 hurricanes during National Oceanic and Atmospheric Administration’s hurricane field program in 2020 are used to study reflectivity (Z) and rainfall rate (RR) (R) relationship (i.e., Z-R relationship). The results show that the Z-R distribution is highly scattered and the scatter increases with RR and reflectivity up to 48 dBZ or 25 mm hr⁻¹, after which it decreases rapidly. The range of the estimated RR from a power-law Z-R relationship can be as large as 50 mm hr⁻¹ at reflectivity of 40 dBZ. The result from random forest regression model demonstrates that including the information of mass-weighted-diameter (D_m) along with radar reflectivity improves the estimated RR significantly.

Accurate specification of hurricane inner-core structure is critical to predicting the evolution of a hurricane. However, observations over hurricane inner cores are generally lacking. Previous studies have emphasized Tail Doppler radar (TDR) data assimilation to improve hurricane inner-core representation. Recently, Doppler wind lidar (DWL) has been used as an observing system to sample hurricane inner-core and environmental conditions. The NOAA P3 Hurricane Hunter aircraft has DWL installed and can obtain wind data over a hurricane’s inner core when the aircraft passes through the hurricane. In this study, we examine the impact of assimilating DWL winds and TDR radial winds on the prediction of Hurricane Earl (2016) with the NCEP operational Hurricane Weather Research and Forecasting (HWRF) system. A series of data assimilation experiments are conducted with the Gridpoint Statistical Interpolation (GSI)-based ensemble-3DVAR hybrid system to identify the best way to assimilate TDR and DWL data into the HWRF forecast system. The results show a positive impact of DWL data on hurricane analysis and prediction. Compared with the assimilation of u and v components, assimilation of DWL wind speed provides better hurricane track and intensity forecasts. Proper choices of data thinning distances (e.g., 5 km horizontal thinning and 70 hPa vertical thinning for DWL) can help achieve better analysis in terms of hurricane vortex representation and forecasts. In the analysis and forecast cycles, the combined TDR and DWL assimilation (DWL wind speed and TDR radial wind, along with other conventional data, e.g., NCEP Automated Data Processing (ADP) data) offsets the downgrade analysis from the absence of DWL observations in an analysis cycle and outperforms assimilation of a single type of data (either TDR or DWL) and leads to improved forecasts of hurricane track, intensity, and structure. Overall, assimilation of DWL observations has been beneficial for analysis and forecasts in most cases. The outcomes from this study demonstrate the great potential of including DWL wind profiles in the operational HWRF system for hurricane forecast improvement. 

The deviation of the mean wind profile from Monin-Obukhov similarity theory (MOST) within the wave boundary layer (WBL) is investigated by combining four levels of turbulence data measured on a fixed platform with wave measurements. The data suggest that the mean wind profile follows MOST under wind-sea conditions because the turbulence statistics and structure are consistent with the attached eddy model. However, pronounced swell-related peaks appeared in the velocity spectra and uw-cospectra under swell conditions. The upward wave-induced stress resulted in a large wind gradient within the WBL when light winds traveled with the swell, while the opposite result was found for the wind-opposite swell. These phenomena were analyzed based on the velocity spectra and turbulence variances. We found that the deviation of the wind profile was due to the longer (shorter) length of the f⁻¹ scaling region appearing in the velocity spectra. 

Observation system experiments (OSEs) are conducted to assess the potential impacts of horizontal line-of-sight wind profile observations from the Aeolus satellite on tropical cyclone (TC) forecasting. The OSEs utilize the operational Hurricane Weather and Research Forecasting (HWRF) model. The OSEs include 226 forecasts from seven TC cases in the Atlantic and Eastern Pacific basins. Comparisons between Aeolus and model background winds show that winds from Aeolus are consistently stronger than those from HWRF. Data assimilation statistics also demonstrate that the greatest potential impacts from the assimilation of Aeolus observations are likely to occur in the upper troposphere and lower stratosphere and within approximately 500 km from the TC centre. For TC forecasting applications, the assimilation of Aeolus observations improves TC intensity and size forecasts in the Eastern Pacific basin, while the results for track forecasts and results from the Atlantic basin are mixed. However, in both basins, the largest and most statistically significant, positive impacts from the assimilation of Aeolus observations occur when reconnaissance flight data are unavailable and during the early stages of TC development. The traditionally used forecast assessments of TC intensity, track and size are rooted in surface-based metrics, and an additional investigation above the surface demonstrated larger improvements from assimilating Aeolus observations on TC wind structure above 400 hPa as compared to the lower troposphere. Several, different assessments throughout this study demonstrate higher uncertainty and the need for special consideration associated with assimilation techniques within 500 km from the TC centre.

Characterizing inflow structure is important to better represent tropical cyclone impacts in numerical models. While much research has considered the impact of storm translation on the distribution of inflow angle, comparatively less research has examined its distribution relative to the environmental wind shear. This study analyzes data from 3,655 dropsondes in 44 storms to investigate the radial and shear-relative distribution of surface inflow angle. Emphasis is placed on its relationship with intensity change. The results show that the radial variation in the inflow angle is small and not significantly dependent on the shear magnitude or intensity change rate. In contrast, the azimuthal distribution of the inflow angle shows a significant asymmetry, with the amplitude of the asymmetry increasing with shear magnitude. The maximum inflow angle is located in the downshear side. The degree of asymmetry is larger in the outer core than in the eyewall. Intensifying storms have a smaller degree of asymmetry than steady-state storms under moderate shear. 

Weather prediction models currently operate within a probabilistic framework for generating forecasts conditioned on recent measurements of Earth’s atmosphere. This framework can be conceptualized as one that approximates parts of a Bayesian posterior density estimated under assumptions of Gaussian errors. Gaussian error approximations are appropriate for synoptic-scale atmospheric flow, which experiences quasi-linear error evolution over time scales depicted by measurements, but are often hypothesized to be inappropriate for highly nonlinear, sparsely-observed mesoscale processes. The current study adopts an experimental regional modeling system to examine the impact of Gaussian prior error approximations, which are adopted by ensemble Kalman filters (EnKFs) to generate probabilistic predictions. The analysis is aided by results obtained using recently-introduced particle filter (PF) methodology that relies on an implicit non-parametric representation of prior probability densities—but with added computational expense. The investigation focuses on EnKF and PF comparisons over month-long experiments performed using an extensive domain, which features the development and passage of numerous extratropical and tropical cyclones. The experiments reveal spurious small-scale corrections in EnKF members, which come about from inappropriate Gaussian approximations for priors dominated by alignment uncertainty in mesoscale weather systems. Similar behavior is found in PF members, owing to the use of a localization operator, but to a much lesser extent. This result is reproduced and studied using a low-dimensional model, which permits the use of large sample estimates of the Bayesian posterior distribution. Findings from this study motivate the use of data assimilation techniques that provide a more appropriate specification of multivariate non-Gaussian prior densities or a multi-scale treatment of alignment errors during data assimilation.

Hurricanes are highly complex geophysical flows that have caused billions of dollars in damage in recent years. Despite the significance of these extreme weather events, the turbulence mechanisms that derive the dynamics of hurricane flow systems are poorly understood and ineffectively parameterized in numerical weather prediction (NWP) models. The objective of this study is to bridge these knowledge gaps by assessing the accuracy and deficiencies of existing horizontal turbulence models in NWPs for hurricane forecasts. In particular, the Weather and Research Forecasting (WRF) Model is employed to conduct 135 simulations of five real hurricanes by varying the grid resolution, turbulence models, and horizontal mixing length values. Decreasing the default horizontal mixing length values both in low and high resolution WRF simulations significantly improves the wind intensity forecasts. This result indicates that the existing horizontal diffusion parameterizations are overly dissipative for hurricane flows, and thus, generate a weaker vortex compared to observations. These deficiencies are shown to stem from the horizontal mixing-length parameterization in WRF that is prescribed as a function of grid size without considering the physics of the flows (e.g., rotation). The paper provides notable insights into the role of turbulent fluxes in simulated hurricane evolutions that can be useful to advance the turbulence parameterizations of NWP models for hurricane forecasts.

Nine sets of 36-h, 10-member, convection-allowing ensemble (CAE) forecasts with 3-km horizontal grid spacing were produced over the conterminous United States for a 4-week period. These CAEs had identical configurations except for their initial conditions (ICs), which were constructed to isolate CAE forecast sensitivity to resolution of IC perturbations and central initial states about which IC perturbations were centered. The IC perturbations and central initial states were provided by limited-area ensemble Kalman filter (EnKF) analyses with both 15- and 3-km horizontal grid spacings, as well as from NCEP’s Global Forecast System (GFS) and Global Ensemble Forecast System. Given fixed-resolution IC perturbations, reducing horizontal grid spacing of central initial states improved ∼1–12-h precipitation forecasts. Conversely, for constant-resolution central initial states, reducing horizontal grid spacing of IC perturbations led to comparatively smaller short-term forecast improvements or none at all. Overall, all CAEs initially centered on 3-km EnKF mean analyses produced objectively better ∼1–12-h precipitation forecasts than CAEs initially centered on GFS or 15-km EnKF mean analyses regardless of IC perturbation resolution, strongly suggesting it is more important for central initial states to possess fine-scale structures than IC perturbations for short-term CAE forecasting applications, although fine-scale perturbations could potentially be critical for data assimilation purposes. These findings have important implications for future operational CAE forecast systems and suggest CAE IC development efforts focus on producing the best possible high-resolution deterministic analyses that can serve as central initial states for CAEs.

Atmospheric dust is an important mass transfer and nutrient supply process in Earth surface ecosystems. For decades, Saharan dust has been hypothesized as a supplier of nutrients to the Amazon Rain Forest and eastern North America. However, isotope studies aimed at detecting Saharan dust in the American sedimentary record have been ambiguous. A large Saharan dust storm emerged off the coast of Africa in June 2020 and extended into southeastern United States. This storm provided a means to evaluate the influence of Saharan dust in North America confirmed by independent satellite and ground observations. Precipitation samples from 17 sites within the National Atmospheric Deposition Program (NADP) were obtained from throughout the southeastern United States prior to, during, and after the arrival of Saharan dust. Precipitation samples were measured for their lead (Pb) isotopic composition, total Pb content, and ²¹⁰Pb activity using multi-collector inductively coupled plasma mass spectrometry. We measured a significant isotopic shift (approximately 0.7 % in the ²⁰⁸Pb/²⁰⁶Pb relative to the ²⁰⁷Pb/²⁰⁶Pb) in precipitation that peaked in late June 2020 when the dust blanketed the southeastern US. However, the magnitude and short time period of the isotopic shift would make it difficult to detect in sedimentary records.

In the past, the Lorenz 1963 and 1969 models have been applied for revealing the chaotic nature of weather and climate and for estimating the atmospheric predictability limit. Recently, an in-depth analysis of classical Lorenz 1963 models and newly developed, generalized Lorenz models suggested a revised view that “the entirety of weather possesses a dual nature of chaos and order with distinct predictability”, in contrast to the conventional view of “weather is chaotic”. The distinct predictability associated with attractor coexistence suggests limited predictability for chaotic solutions and unlimited predictability (or up to their lifetime) for non-chaotic solutions. Such a view is also supported by a recent analysis of the Lorenz 1969 model that is capable of producing both unstable and stable solutions. While the alternative appearance of two kinds of attractor coexistence was previously illustrated, in this study, multistability (for attractor coexistence) and monostability (for single type solutions) are further discussed using kayaking and skiing as an analogy. Using a slowly varying, periodic heating parameter, we additionally emphasize the predictable nature of recurrence for slowly varying solutions and a less predictable (or unpredictable) nature for the onset for emerging solutions (defined as the exact timing for the transition from a chaotic solution to a non-chaotic limit cycle type solution). As a result, we refined the revised view outlined above to: “The atmosphere possesses chaos and order; it includes, as examples, emerging organized systems (such as tornadoes) and time varying forcing from recurrent seasons”. In addition to diurnal and annual cycles, examples of non-chaotic weather systems, as previously documented, are provided to support the revised view.

This study reviews the recent addition of dropwindsonde wind data near the tropical cyclone (TC) center as well as the first-time addition of high-density, flight-level reconnaissance observations (HDOBs) into the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS). The main finding is that the additional data has profound positive impacts on subsequent TC track forecasts. For TCs in the North Atlantic (NATL) basin, statistically significant improvements in track extend through 4-5 days during reconnaissance periods. Further assessment suggests that greater improvements might also be expected at days 6-7. This study also explores the importance of comprehensively assessing data impact. For example, model or data assimilation changes can affect the so-called “early” and “late” versions of the forecast very differently. It is also important to explore different ways to describe the error statistics. In several instances the impacts of the additional data strongly differ depending on whether one examines the mean or median errors. The results demonstrate the tremendous potential for further improving TC forecasts. The data added here were already operationally transmitted and assimilated by other systems at NCEP, and many further improvements likely await with improved use of these and other reconnaissance observations. This demonstrates the need of not only investing in data assimilation improvements, but also enhancements to observational systems in order to reach next-generation hurricane forecasting goals. 

The relationship between deep-layer environmental wind shear direction and tropical cyclone (TC) boundary layer thermodynamic structures is explored in multiple independent databases. Analyses derived from the tropical cyclone buoy database (TCBD) show that when TCs experience northerly-component shear, the 10-m equivalent potential temperature (θ_e) tends to be more symmetric than when shear has a southerly component. The primary asymmetry in θ_e in TCs experiencing southerly-component shear is radially outwards from twice the radius of maximum wind speed, with the left-of-shear quadrants having lower θ_e by 4–6 K than the right-of-shear quadrants. As with the TCBD, an asymmetric (symmetric) distribution of 10-m θ_e for TCs experiencing southerly-component (northerly-component) shear was found using composite observations from dropsondes. These analyses show that differences in the degree of symmetry near the sea surface extend through the depth of the boundary layer. Additionally, mean dropsonde profiles illustrate that TCs experiencing northerly-component shear are more potentially unstable between 500 m and 1000 m altitude, signaling a more favorable environment for the development of surface-based convection in rainband regions. Analyses from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) database show that subsequent strengthening (weakening) for TCs in the Atlantic Basin preferentially occurs in northerly-component (southerly-component) deep-layer environmental wind shear environments which further illustrates that the asymmetric distribution of boundary layer thermodynamics is unfavorable for TC intensification. These differences emphasize the impact of deep-layer wind shear direction on TC intensity changes which likely result from the superposition of large-scale advection with the shear-relative asymmetries in TC structure.

In this study, a set of deep convolutional neural networks (CNNs) was designed for estimating the intensity of tropical cyclones (TCs) over the Northwest Pacific Ocean from the brightness temperature data observed by the Advanced Himawari Imager onboard the Himawari-8 geostationary satellite. We used 97 TC cases from 2015 to 2018 to train the CNN models. Several models with different inputs and parameters are designed. A comparative study showed that the selection of different infrared (IR) channels has a significant impact on the performance of the TC intensity estimate from the CNN models. Compared with the ground truth Best Track data of the maximum sustained wind speed, with a combination of four channels of data as input, the best multicategory CNN classification model has generated a fairly good accuracy (84.8%) and low root mean square error (RMSE, 5.24 m/s) and mean bias (-2.15 m/s) in TC intensity estimation. Adding attention layers after the input layer in the CNN helps to improve the model accuracy. The model is quite stable even with the influence of image noise. To reduce the side-effect of the very unbalanced distribution of TC category samples, we introduced a focal_loss function into the CNN model. After we transformed the multiclassification problem into a binary classification problem, the accuracy increased to 88.9%, and the RMSE and the mean bias are significantly reduced to 4.62 and -0.76 m/s, respectively. The results show that our CNN models are robust in estimating TC intensity from geostationary satellite images.

Typhoon Fanapi (2010) made landfall in Hualien in Taiwan on 0100 UTC 19 September 2010 and left Taiwan on 1200 UTC 19 September 2010, producing heavy rainfall and floods. Fanapi’s eyewall was disrupted by the Central Mountain Range (CMR) and reorganized after leaving the CMR. High-resolution simulations (nested down to 1-km horizontal grid size) using the Advanced Research Weather Research and Forecast (WRF) model, one simulation using the full terrain (CTL) and another set of simulations where the terrain on Taiwan was removed, were analyzed. Precipitation areas were classified into different sub-regions by a convective-stratiform separation algorithm to assess the impact of precipitation structure on Fanapi’s eyewall evolution. The percentage of deep convection increased from 9% to 20% when Fanapi underwent an eyewall reorganization process while departing the CMR. In the absence of terrain, moderate convection occupied most of the convective regions during the period when Fanapi moved across Taiwan Island. The low-level total vorticity stretching within the convective, stratiform and weak echo regions in the no-terrain experiment were of similar magnitudes, but the total vorticity stretching within the convective region at low levels was dominant in the CTL experiment. Total vorticity stretching in the region of deep convection increased after eyewall reorganization, and later became stronger than that in the moderate convection region. In the absence of the CMR, total vorticity stretching in moderate convection dominated. The total vorticity stretching within the deep convective region in the CTL experiment played an essential role in the reorganization of Fanapi’s eyewall through a bottom-up process.

Since 2005, NOAA has conducted the annual Intensity Forecasting Experiment (IFEX), led by scientists from the Hurricane Research Division at NOAA’s Atlantic Oceanographic and Meteorological Laboratory. They partner with NOAA’s Aircraft Operations Center, who maintain and operate the WP-3D and G-IV Hurricane Hunter aircraft, and NCEP’s National Hurricane Center and Environmental Modeling Center, who task airborne missions to gather data used by forecasters for analysis and forecasting and for ingest into operational numerical weather prediction models. The goal of IFEX is to improve tropical cyclone (TC) forecasts using an integrated approach of analyzing observations from aircraft, initializing and evaluating forecast models with those observations, and developing new airborne instrumentation and observing strategies targeted at filling observing gaps and maximizing the data’s impact in model forecasts. This summary article not only highlights recent IFEX contributions towards improved TC understanding and prediction, but also reflects more broadly on the accomplishments of the program during the 16 years of its existence. It describes how IFEX addresses high-priority forecast challenges, summarizes recent collaborations, describes advancements in observing systems monitoring structure and intensity, as well as in assimilation of aircraft data into operational models, and emphasizes key advances in understanding of TC processes, particularly those that lead to rapid intensification. The article concludes by laying the foundation for the “next generation” of IFEX as it broadens its scope to all TC hazards, particularly rainfall, storm-surge inundation, and tornadoes, that have gained notoriety during the last few years after several devastating landfalling TCs.

Tropical cyclones (TCs), especially landfalling intense storms often pose serious threats to life and property in coastal areas. Although TC track forecast skill has been improved in the past decades, the progress of advancing the intensity forecast lags that of the track forecast. One possible limiting factor is the absence of ocean surface waves in forecast systems. To better represent the interaction of TC and underlying ocean, a regional atmosphere-ocean-wave coupled model is employed in this study. Twenty-one TCs of a whole year in 2013 are retrospectively simulated through twin simulations, a Control and a Fully coupled run. Results show that TC intensity bias has been significantly reduced in the fully coupled simulation, in which five ocean surface wave related physical processes are considered, including wave modulation of momentum flux, sea spray effect on enthalpy flux, surface current and Stokes drift on air sea flux, non-breaking wave induced mixing in the upper ocean as well as rain induced ocean surface cooling. A case study approach is used to diagnose the effect of individual surface wave related physical process on TC simulations. Similar to the effect of sea spray, surface waves also act as positive feedback on TC intensification by modulating air-sea momentum flux. Absolute angular momentum budget analysis suggests that larger radial inflows and stronger updrafts near the eyewall promote the radial and vertical advections of absolute angular momentum and in turn lead to a stronger TC in Fully coupled simulation. The TC structure and size agree better with observations in Fully coupled simulation.

This study investigates the atmospheric boundary layer structure based on multiple-level tower observations with a height of 350 m during the landfall of Super Typhoon Mangkhut (2018). Results show a layer of log wind profile outside of the radius of maximum wind speed with a height of 100 m or larger. The log layer height increases with the wind speed. The height of the constant flux layer reaches ~ 300 m for 10-m wind speeds less than 13 m s⁻¹ while this height decreases with the wind speed. Momentum fluxes and turbulent kinetic energy increase with the wind speed at all vertical levels. The drag coefficient and surface roughness length estimated at the tower location have values of 7.3 × 10^–3 and 0.09 m, respectively, which are independent of wind speed. The estimated vertical eddy diffusivity and mixing length increase with height up to ~ 160 m and then slowly decrease with height. The vertical eddy diffusivity increases with the wind speed while the vertical mixing length has no dependence on the wind speed. Comparing our results with previous work indicates that the vertical eddy diffusivity is larger over land than over ocean at a given wind speed range.

Statistical significance tests can inform whether differences between two samples are real or due to sampling error. Forecasts are serially correlated because the first guess for each model cycle is a forecast from the previous one, and this must be accounted for in statistical tests on the impact of new observing systems or model system techniques. Prior studies showed that tropical cyclone track forecasts created every 24 h or 12 h were serially ­correlated so that only every other forecast was independent of the others. Forecasts are now initialized more frequently than those used in the earlier studies (every 6 h), requiring a reassessment of the serial correlation. The current study calculates the effective time ­between independent samples based on two distinct techniques for both tropical cyclone track and intensity forecasts. The calculated effective time varies by storm, forecast, and technique, though it appears that the separation times for both track and intensity are about 12 h/18 h/24 h from lead times 12-26 h/42-96 h/102-120 h, respectively. These calculations may be used to best calculate whether differences between tropical cyclone track and ­intensity forecasts from various models are statistically significant, and to inform the ­efficient design of tests of new systems.

In this first part of a two-part study, the three-dimensional structure of the inner-core boundary layer (BL) is investigated in a full-physics simulation of Hurricane Irma (2017). The BL structure is highlighted during periods of intensity change, with focus on features and mechanisms associated with storm decay. The azimuthal structure of the BL is shown to be linked to the vertical wind shear and storm motion. The BL inflow becomes more asymmetric under increased shear. As BL inflow asymmetry amplifies, asymmetries in the low-level primary circulation and thermodynamic structure develop. A mechanism is identified to explain the onset of pronounced structural asymmetries in coincidence with external forcing (e.g., through shear) that would amplify BL inflow along limited azimuth. The mechanism assumes enhanced advection of absolute angular momentum along the path of the amplified inflow (e.g., amplified downshear), which results in local spinup of the vortex and development of strong supergradient flow downwind and along the BL top. The associated agradient force results in the outward acceleration of air immediately above the BL inflow, affecting fields including divergence, vertical motion, entropy advection, and inertial stability. In this simulation, descending inflow in coincidence with amplified shear is identified as the conduit through which low-entropy air enters the inner-core BL, thereby hampering convection downwind and resulting in storm decay.

This study examines how varying wind profile coverages in the tropical cyclone (TC) core, near-environment and broader synoptic environment affect the structure and evolution of a simulated Atlantic hurricane through data assimilation. Three sets of observing system simulation experiments (OSSEs) are examined in this paper. The first experiment establishes a benchmark for the case study specific to the forecast system used by assimilating idealized profiles throughout the parent domain. The second presents how TC analyses and forecasts respond to varying the coverage of swaths produced by polar-orbiting satellites of idealized wind profiles. The final experiment assesses the role of TC inner-core observations by systematically removing them radially from the center. All observations are simulated from a high-resolution regional “Nature Run” of a hurricane and the tropical atmosphere, assimilated an Ensemble Square-Root Kalman Filter and the Hurricane Weather and Research Forecast (HWRF) regional model. Results compare observation impact to the analyses, domain-wide and TC centric error statistics, and TC structural differences among the experiments. The study concludes that the most accurate TC representation is a result of the assimilation of collocated and uniform thermodynamic and kinematics observations. Intensity forecasts are improved with increased inner core wind observations, even if the observations are only available once daily. Domain-wide root-mean-square errors are significantly reduced when the TC is observed during a period of structural change, like rapid intensification. The experiments suggest the importance of wind observations and the role of inner-core surveillance when analyzing and forecasting realistic TC structure.

This study analyzes GPS dropsonde data in multiple tropical cyclones from 1997 to 2017 to investigate the boundary layer structure with a focus on helicity distribution. A helicity-based method for boundary layer height is developed and evaluated by comparing it to other boundary layer height scales including the inflow layer depth, height of the maximum tangential wind speed and thermodynamic mixed layer depth. Our dropsonde composites confirmed the radial variations of these boundary layer heights seen in previous studies. The results show that the boundary layer height defined by the maximum vertical gradient of helicity is closest to the height of the maximum tangential wind speed or jet height and is located between the inflow layer depth and thermodynamic mixed layer height in all intensity groups. All three kinematic height scales generally decrease with storm intensity at a given radius. These kinematic height scales converge in the major hurricane group, while the inflow layer depth is much larger than the other two height scales in the tropical storm group. The maximum normalized helicity is located at 100–200 m altitude which is close to the height of the maximum inflow. Both front-back and downshear-upshear asymmetries are observed in the 0–1 km layer integrated helicity in the inner core region of a storm, and the helicity on the front and downshear sides is larger in all intensity groups. The results also show that the helicity magnitude is generally larger in the boundary layer of stronger storms. Application of helicity to quantify turbulent characteristics in the boundary layer is discussed.

Horizontal homogeneity is typically assumed in the design of planetary boundary layer (PBL) parameterizations in weather prediction models. Consistent with this assumption, PBL schemes with predictive equations for subgrid turbulence kinetic energy (TKE) typically neglect advection of TKE. However, tropical cyclone (TC) boundary layers are inhomogeneous, particularly in the eyewall. To gain further insight, this study examines the effect of advection of TKE using the Mellor-Yamada-Nakanishi-Niino (MYNN) PBL scheme in idealized TC simulations. The analysis focuses on two simulations, one that includes TKE advection (CTL) and one that does not (NoADV). Results show that relatively large TKE in the eyewall above 2 km is predominantly attributable to vertical advection of TKE in CTL. Interestingly, buoyancy production of TKE is negative in this region in both simulations; thus, buoyancy effects cannot explain observed columns of TKE in TC eyewalls. Both horizontal and vertical advection of TKE tends to reduce TKE and vertical viscosity (K_m) in the near-surface inflow layer, particularly in the eyewall of TCs. Results also show that the simulated TC in CTL has slightly stronger maximum winds, slightly smaller radius of maximum wind (RMW), and ~5% smaller radius of gale-force wind than in NoADV. These differences are consistent with absolute angular momentum being advected to smaller radii in CTL. Sensitivity simulations further reveal that the differences between CTL and NoADV are more attributable to vertical advection (rather than horizontal advection) of TKE. Recommendations for improvements of PBL schemes that use predictive equations for TKE are also discussed.

Boundary layer turbulent processes affect tropical cyclone (TC) structure and intensity change. However, uncertainties in the parameterization of the planetary boundary layer (PBL) under high-wind conditions remain challenging, mostly due to limited observations. This study presents and evaluates a framework of numerical simulation that can be used for a small-domain [O(5 km)] large-eddy simulation (LES) and single-column modeling (SCM) to study the TC boundary layer. The framework builds upon a previous study that uses a few input parameters to represent the TC vortex and adds a simple nudging term for temperature and moisture to account for the complex thermodynamic processes in TCs. The reference thermodynamic profiles at different wind speeds are retrieved from a composite analysis of dropsonde observations of mature hurricanes. Results from LES show that most of the turbulence kinetic energy and vertical momentum flux is associated with resolved processes when horizontal grid spacing is O(10 m). Comparison to observations of turbulence variables such as momentum flux, effective eddy viscosity, and turbulence length scale show that LES produces reasonable results but highlight areas where further observations are necessary. LES results also demonstrate that compared to a classic Ekman-type boundary layer, the TC boundary layer is shallower, develops steady conditions much quicker, and exhibits stronger wind speed near the surface. The utility of this framework is further highlighted by evaluating a first-order PBL parameterization, suggesting that an asymptotic turbulence length scale of 40 m produces a good match to LES results.

This study investigates the precipitation symmetrization preceding rapid intensification (RI) of tropical cyclones (TCs) experiencing vertical wind shear by analyzing numerical simulations of Typhoon Mujigae (2015) with warm (CTL) and relatively cool (S1) sea surface temperatures (SSTs). A novel finding is that precipitation symmetrization is maintained by the continuous development of deep convection along the inward flank of a convective precipitation shield (CPS), especially in the downwind part. Beneath the CPS, downdrafts flush the boundary layer with low-entropy parcels. These low-entropy parcels do not necessarily weaken the TCs; instead, they are “recycled” in the TC circulation, gradually recovered by positive enthalpy fluxes, and develop into convection during their propagation toward a downshear convergence zone. Along-trajectory vertical momentum budget analyses reveal the predominant role of buoyancy acceleration in the convective development in both experiments. The boundary layer recovery is more efficient for warmer SST, and the stronger buoyancy acceleration accounts for the higher probability of these parcels developing into deep convection in the downwind part of the CPS, which helps maintain the precipitation symmetrization in CTL. In contrast, less efficient boundary layer recovery and less upshear deep convection hinder the precipitation symmetrization in S1. These findings highlight the key role of boundary layer recovery in regulating the precipitation symmetrization and upshear deep convection, which further accounts for an earlier RI onset timing of the CTL TC. The inward rebuilding pathway also illuminates why deep convection is preferentially located inside the radius of maximum wind of sheared TCs undergoing RI.

Horizontal grid spacings of numerical weather prediction models are rapidly approaching O (1 km) and have become comparable with the dominant length scales of flows in the boundary layer; within such “gray-zone”, conventional planetary boundary layer (PBL) parameterization schemes start to violate basic design assumptions. Scale-aware PBL schemes have been developed recently to address the gray-zone issue. By performing WRF simulations of Hurricane Earl (2010) at sub-kilometer grid spacings, this study investigates the effect of the scale-aware Shin-Hong (SH) scheme on the tropical cyclone (TC) intensification and structural changes in comparison to the non-scale-aware YSU scheme it is built upon. Results indicate that SH tends to produce a stronger TC with a more compact inner core than YSU. At early stages, the scale-aware coefficients in SH gradually decrease as the diagnosed boundary layer height exceeds the horizontal grid spacing. This scale-aware effect is most prominent for the nonlocal subgrid-scale vertical turbulent fluxes, in the non-precipitation regions radially outside of the convective rainband, and from the early stage through the middle of rapid intensification (RI) phase. Both the scale awareness and different parameterization of the nonlocal turbulent heat flux in SH reduce the parameterized vertical turbulent mixing, which further induces stronger radial inflows and helps retain more water vapor in the boundary layer. The resulting stronger moisture convergence and diabatic heating near the TC center account for the faster inner-core contraction before RI onset and the higher intensification rate during the RI period. Potential issues of applying these two PBL schemes in TC simulations and suggestions for improvements are discussed.

As part of the NASA Earth Venture-Instrument program, the Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission, to be launched in January 2022, will deliver unprecedented rapid-update microwave measurements over the tropics that can be used to observe the evolution of the precipitation and thermodynamic structure of tropical cyclones (TCs) at meso- and synoptic scales. TROPICS consists of six CubeSats, each hosting a passive microwave radiometer that provides radiance observations sensitive to atmospheric temperature, water vapor, precipitation, and precipitation-size ice particles. In this study, the impact of TROPICS all-sky radiances on TC analyses and forecasts is explored through a regional mesoscale observing system simulation experiment (OSSE). The results indicate that the TROPICS all-sky radiances can have positive impacts on TC track and intensity forecasts, particularly when some hydrometeor state variables and other state variables of the data assimilation system that are relevant to cloudy radiance assimilation are updated. The largest impact on the model analyses is seen in the humidity fields, regardless of whether or not there are radiances assimilated from other satellites. TROPICS radiances demonstrate large impact on TC analyses and forecasts when other satellite radiances are absent. The assimilation of the all-sky TROPICS radiances without default radiances leads to a consistent improvement in the low- and mid-tropospheric temperature and wind forecasts throughout the five-day forecasts, but only up to 36 h lead time in the humidity forecasts at all pressure levels. This study illustrates the potential benefits of TROPICS data assimilation for TC forecasts and provides a potentially streamlined pathway for transitioning TROPICS data from research to operations post-launch.

As global data assimilation systems continue to evolve, Observing System Simulation Experiments (OSSEs) need to be updated to accurately quantify the impact of proposed observing technologies in weather forecasting. Earlier OSSEs with radio occultation (RO) observations have been updated and the impact of the originally proposed Constellation Observing Satellites for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) mission, with a high-inclination and low-inclination component, has been investigated by using the operational data assimilation system at NOAA and a 1-dimensional bending angle RO forward operator. It is found that the impact of the low-inclination component of the originally planned COSMIC-2 mission (now officially named COSMIC-2) has significantly increased as compared to earlier studies, and significant positive impact is now found globally in terms of mass and wind fields. These are encouraging results as COSMIC-2 was successfully launched in June 2019 and data have been recently released to operational weather centers. Earlier findings remain valid indicating that globally distributed RO observations are more important to improve weather prediction globally than a denser sampling of the tropical latitudes. Overall, the benefits reported here from assimilating RO soundings are much more significant than the impacts found in previous OSSEs. This is largely attributed to changes in the data assimilation and forecast system and less to the more advanced 1-dimensional forward operator chosen for the assimilation of RO observations.

Although some recent progress has been made in operational tropical cyclone (TC) intensity forecasting, the prediction of rapid intensification (RI) remains a challenging problem. To document RI forecast progress, deterministic and probabilistic operational intensity models used by the National Hurricane Center (NHC) are briefly reviewed. Results show that none of the deterministic models had RI utility from 1991 to about 2015 due to very low probability of detection, very high false alarm ratio, or both. Some ability to forecast RI has emerged since 2015, with dynamical models being the best guidance for the Atlantic and statistical models the best RI guidance for the eastern North Pacific. The first probabilistic RI guidance became available in 2001, with several upgrades since then leading to modest skill in recent years. A tool introduced in 2018 (DTOPS) is currently the most skillful among NHC’s probabilistic RI guidance. To measure programmatic progress in forecasting RI, the Hurricane Forecast Improvement Program has introduced a new RI metric that uses the traditional mean absolute error but restricts the sample to only those cases where RI occurred in the verifying best track or was forecast. By this metric, RI forecasts have improved by ~20–25% since the 2015–2017 baseline period.

Major Atlantic hurricanes Irma, Jose, and Maria of 2017 reached their peak intensity in September while traveling over the tropical North Atlantic Ocean and Caribbean Sea, where both atmospheric and ocean conditions were favorable for intensification. In-situ and satellite ocean observations revealed that conditions in these areas exhibited: (i) sea surface temperatures above 28°C; (ii) upper-ocean heat content above 60 kJ cm^-2; and (iii) the presence of low-salinity barrier layers associated with a larger-than-usual extension of the Amazon and Orinoco riverine plumes. Proof-of-concept coupled ocean-hurricane numerical model experiments demonstrated that the accurate representation of such ocean conditions led to an improvement in the simulated intensity of Hurricane Maria for the 3 days preceding landfall in Puerto Rico, when compared to an experiment without the assimilation of ocean observations. Without the assimilation of ocean observations, upper-ocean thermal conditions were generally colder than observations, resulting in reduced air-sea enthalpy fluxes - enthalpy fluxes are more realistically simulated when the upper-ocean temperature and salinity structure is better represented in the model. Our results further showed that different components of the ocean observing system provide valuable information in support of improved TC simulations, and that assimilation of underwater glider observations alone provided the largest improvement of the total improvement over the 24-hour time frame before landfall. Our results therefore indicated that ocean conditions were relevant for more realistically simulating Hurricane Maria’s intensity. However, further research based on a comprehensive set of hurricane cases is required to confirm robust improvements to forecast systems.

Flight‐level data and global positioning system dropwindsonde observations collected from more than 187 flights into 19 tropical cyclones were used to examine why different planetary boundary layer parameterization schemes applied to hurricane models produce diverse forecasts of structure and intensity change. Two popular, yet diverse, physics schemes, namely, the GFS K‐Profile and a 1.5‐order turbulence kinetic energy closure parameterization from NOAA's next‐generation FV3‐based Hurricane Analysis and Forecast System were used. It was found that uncertainty related to some key variables used in the parameterization of the eddy diffusivity, K_m, led to diverse solutions. For a given grid resolution, both parameterization schemes converged to a similar forecast state provided those uncertainties could be identified and improved based on observations. This is important for providing a generalized framework for the development and evaluation of parameterization schemes in operational models that resemble reality. This study also indicates that the shape of the K_m profile is equally important as its maximum value. The smaller the K_m near the surface, the stronger the inflow in the boundary layer.

The prediction of rapid intensification (RI) in tropical cyclones (TCs) is a challenging problem. In this study, the RI process and factors contributing to it are compared for two TCs: an axis-symmetric case (Hurricane Irma, 2017) and an asymmetric case (Hurricane Michael, 2018). Both Irma and Michael became major hurricanes that made significant impacts in the United States. The Hurricane Weather Research and Forecasting (HWRF) Model was used to examine the connection between RI with forcing from the large-scale environment and the subsequent evolution of TC structure and convection. The observed large-scale environment was reasonably reproduced by HWRF forecasts. Hurricane Irma rapidly intensified in an environment with weak-to-moderate vertical wind shear (VWS), typically favorable for RI, leading to the symmetric development of vortical convective clouds in the cyclonic, vorticity-rich environment. Conversely, Hurricane Michael rapidly intensified in an environment of strong VWS, typically unfavorable for RI, leading to major asymmetries in the development of vortical convective clouds. The tangential wind momentum budget was analyzed for these two hurricanes to identify similarities and differences in the pathways to RI. Results suggest that eddy transport terms associated with convective processes positively contributed to vortex spin up in the early stages of RI and inhibited spin up in the later stages of RI in both TCs. In the early stages of RI, the mean transport terms exhibited notable differences in these TCs; they dominated the spin-up process in Irma and were of secondary importance to the spin-up process in Michael. Favorable aspects of the environment surrounding Michael appeared to aid in the RI process despite hostile VWS.

The early stages of a tropical cyclone can be a challenge to forecast, as a storm consolidates and begins to grow based on the local and environmental conditions. A high-resolution ensemble of the Hurricane Analysis and Forecast System (HAFS) is used to study the early intensification of Hurricane Dorian, a catastrophic 2019 storm in which the early period proved challenging for forecasters. There was a clear connection in the ensemble between early storm track and intensity: stronger members moved more northeast initially, although this result did not have much impact on the long-term track. The ensemble results show several key factors determining the early evolution of Dorian. Large-scale divergence northeast of the tropical cyclone (TC) appeared to favor intensification, and this structure was present at model initialization. There was also greater moisture northeast of the TC for stronger members at initialization, favoring more intensification and downshear development of the circulation as these members evolved. This study highlights the complex interplay between synoptic and storm scale processes in the development and intensification of early-stage tropical cyclones.

NOAA’s Hurricane Analysis and Forecast System (HAFS) is an evolving FV3-based hurricane modeling system that is expected to replace the operational hurricane models at the National Weather Service. Supported by the Hurricane Forecast Improvement Program (HFIP), global-nested and regional versions of HAFS were run in real-time in 2019 to create the first baseline for the HAFS advancement. In this study, forecasts from the global-nested configuration of HAFS (HAFS-globalnest) are evaluated and compared with other operational and experimental models. The forecasts by HAFS-globalnest covered the period from July through October during the 2019 hurricane season. Tropical cyclone (TC) track, intensity, and structure forecast verifications are examined. HAFS-globalnest showed track skill superior to several operational hurricane models and comparable intensity and structure skill, although the skill in predicting rapid intensification was slightly inferior to the operational model skill. HAFS-globalnest correctly predicted that Hurricane Dorian would slow and turn north in the Bahamas and also correctly predicted structural features in other TCs such as a sting jet in Hurricane Humberto during extratropical transition. Humberto was also a case where HAFS-globalnest had better track forecasts than a regional version of HAFS (HAFS-SAR) due to a better representation of the large-scale flow. These examples and others are examined through comparisons with airborne tail Doppler radar from the NOAA WP-3D to provide a more detailed evaluation of TC structure prediction. The results from this real-time experiment motivates several future model improvements, and highlights the promise of HAFS-globalnest for improved TC prediction.

Polarimetric radar observations from the NEXRAD WSR-88D operational radar network in the contiguous United States, routinely available since 2013, are used to reveal three prominent microphysical signatures in landfalling tropical cyclones: (1) hydrometeor size sorting within the eyewall convection; (2) vertical displacement of the melting layer within the inner core; and (3) dendritic growth layers within stratiform regions of the inner core. Size sorting signatures within eyewall convection are observed with greater frequency and prominence in more intense hurricanes, and are observed predominantly within the deep-layer environmental wind shear vector-relative quadrants that harbor the greatest frequency of deep convection (i.e., downshear and left-of-shear). Melting layer displacements are shown to exceed 1 km in altitude compared to melting layer altitudes in outer rainbands and are complemented by analyses of archived dropsonde data. Dendritic growth and attendant snow aggregation signatures in the inner core are found to occur more often when echo top altitudes are low (≤10 km ASL), nearer the –15°C isotherm commonly associated with dendritic growth. These signatures, uniquely observed by polarimetric radar, provide greater insight into the physical structure and thermodynamic characteristics of tropical cyclones, which are important for improving rainfall estimation and the representation of tropical cyclones in numerical models.

Delay-Doppler maps (DDMs) are generally the lowest level of calibrated observables produced from global navigation satellite system reflectometry (GNSS-R). A forward model is presented to relate the DDM, in units of absolute power at the receiver, to the ocean surface wind field. This model and the related Jacobian are designed for use in assimilating DDM observables into weather forecast models. Given that the forward model represents a full set of DDM measurements, direct assimilation of this lower level data product is expected to be more effective than using individual specular-point wind speed retrievals. The forward model is assessed by comparing DDMs computed from hurricane weather research and forecasting (HWRF) model winds against measured DDMs from the Cyclone Global Navigation Satellite System (CYGNSS) Level 1a data. Quality controls are proposed as a result of observed discrepancies due to the effect of swell, power calibration bias, inaccurate specular point position, and model representativeness error. DDM assimilation is demonstrated using a variational analysis method (VAM) applied to three cases from June 2017, specifically selected due to the large deviation between scatterometer winds and European Centre for Medium-Range Weather Forecasts (ECMWF) predictions. DDM assimilation reduced the root-mean-square error (RMSE) by 15%, 28%, and 48%, respectively, in each of the three examples.

Direct remote‐sensing observations (e.g., radar backscatter, radiometer brightness temperature, or radio occultation bending angle) are often more effective for use in data assimilation (DA) than the corresponding geophysical retrievals (e.g., ocean surface winds, soil moisture, or atmospheric water vapor). In the particular case of Global Navigation Satellite System Reflectometry (GNSS‐R), the lower‐level delay‐Doppler map (DDM) observable shows a complicated relationship with the ocean surface wind field. Prior studies have demonstrated DA using GNSS‐R wind retrievals inferred from DDMs. The complexity of the DDM dependence on winds, however, suggests that the alternative approach of ingesting DDM observables directly into DA systems, without performing a wind retrieval, may be beneficial. We demonstrate assimilation of DDM observables from the NASA Cyclone Global Navigation Satellite System (CYGNSS) mission into global ocean surface wind analyses using a two‐dimensional variational analysis method. Bias correction and quality‐control methods are described. Several models for the required observation‐error covariance matrix are developed and evaluated, with the conclusion that a diagonal matrix performs as well as a fully populated matrix empirically tuned to a large ensemble of CYGNSS observation data. The 10‐m surface winds from the European Centre for Medium‐Range Weather Forecasts (ECMWF) operational forecast are used as the background (i.e., prior in the variational analysis). Results are compared with independent scatterometer (the advanced scatterometer (ASCAT), the oceansat‐2 Scatterometer (OSCAT)) winds. For one month (June 2017) of data, the root‐mean‐square difference (RMSD) was reduced from 1.17 to 1.07 m·s⁻¹ and bias from −0.14 to −0.08 m·s⁻¹ for the wind speed at the specular point. Within a 150‐km wide swath along the specular point track, the RMSD was reduced from 1.20 to 1.13 m·s⁻¹. These RMSD and bias statistics are smaller than other CYGNSS wind products available at this time.

The turbulent structure within the marine atmospheric boundary layer is investigated based on four levels of observations at a fixed marine platform. During and before a cold front, the ocean surface is dominated by wind, sea, and swell waves, respectively, affording the opportunity to test the theory recently proposed in laboratory experiments for flat land surfaces. The results reveal that the velocity spectra follow a k ^-1 law within the intermediate wavenumber (k) range immediately below the inertial subrange during the cold front. A logarithmic height dependence of the horizontal velocity variances is also observed above the height of 20 m, while the vertical velocity variances increase with increasing height following a power law of 2/3. These features confirm the Attached Eddy Model and the “top-down model” of turbulence over the ocean surface. However, the behavior of velocity variances under swell conditions is much different from those during the cold front, although a remarkable k ^-1 law can be observed in the velocity spectra. The quadrant analysis of the momentum flux also shows a significantly different result for the two conditions.

Sea-to-air heat fluxes are the energy source for tropical cyclone (TC) development and maintenance. In the bulk aerodynamic formulae, these fluxes are a function of surface wind speed (U₁₀) and air-sea temperature and moisture disequilibrium (ΔT and Δq, respectively). While many studies have explained TC intensification through the mutual dependence between increasing U₁₀ and increasing sea-to-air heat fluxes, recent studies found TC intensification can occur through deep convective vortex structures that obtain their local buoyancy from sea-to-air moisture fluxes, even under relatively low-wind conditions. Herein, a new perspective on the bulk aerodynamic formulae is introduced to evaluate the relative contribution of wind-driven (U₁₀) and thermodynamically-driven (ΔT and Δq) ocean heat-uptake. Previously unnoticed salient properties of these formulae, reported here, are: (1) these functions are hyperbolic; and, (2) increasing Δq is an efficient mechanism for enhancing the fluxes. This new perspective was used to investigate surface heat fluxes in six TCs during phases of steady state intensity (SS), slow intensification (SI), and rapid intensification (RI). A capping of wind-driven heat-uptake was found during periods of SS, SI, and RI. Compensation by larger values of Δq>5 g kg^-1 at moderate values of U₁₀ led to intense inner-core moisture fluxes >600 W m^-2 during RI. Peak values in Δq preferentially occurred over oceanic regimes with higher sea surface temperature (SST) and upper-ocean heat content. Thus, increasing SST and Δq is a very effective way to increase surface heat fluxes—this can be easily achieved as a TC moves over deeper warm oceanic regimes.

The intensity and structure of simulated tropical cyclones (TCs) are known to be sensitive to the planetary boundary layer (PBL) parameterization in numerical weather prediction models. In this paper, we use an idealized version of the Hurricane Weather Research and Forecast system (HWRF) with constant sea-surface temperature (SST) to examine how the configuration of the PBL scheme used in the operational HWRF affects TC intensity change (including rapid intensification) and structure. The configuration changes explored in this study include disabling non-local vertical mixing, changing the coefficients in the stability functions for momentum and heat, and directly modifying the Prandtl number (Pr), which controls the ratio of momentum to heat and moisture exchange in the PBL. Relative to the control simulation, disabling non-local mixing produced a ~15% larger storm that intensified more gradually, while changing the coefficient values used in the stability functions had little effect. Varying Pr within the PBL had the greatest impact, with the largest Pr (~1.6 versus ~0.8) associated with more rapid intensification (~38 versus 29 m s⁻¹ per day) but a 5–10 m s⁻¹ weaker intensity after the initial period of strengthening. This seemingly paradoxical result is likely due to a decrease in the radius of maximum wind (~15 versus 20 km), but smaller enthalpy fluxes, in simulated storms with larger Pr. These results underscore the importance of measuring the vertical eddy diffusivities of momentum, heat, and moisture under high-wind, open-ocean conditions to reduce uncertainty in Pr in the TC PBL.

This study estimates the random error variances and standard deviations (STDs) for four data sets: Global Hawk (GH) dropsondes (DROP), the High-Altitude Monolithic Microwave Integrated Circuit Sounding Radiometer (HAMSR) aboard the GH, the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis, and the Hurricane Weather Research and Forecasting (HWRF) model, using the three-cornered hat (3CH) method. These estimates are made during the 2016 Sensing Hazards with Operational Unmanned Technology (SHOUT) season in the environment of four tropical cyclones from August to October. For temperature and specific and relative humidity, the ERA5, HWRF, and DROP data sets all have similar magnitudes of errors, with ERA5 having the smallest. The error STDs of temperature and specific humidity are less than 0.8 K and 1.0 g kg^-1 over most of the troposphere, while relative humidity error STDs increase from less than 5% near the surface to between 10 and 20% in the upper troposphere. The HAMSR bias-corrected data have larger errors, with estimated error STDs of temperature and specific humidity in the lower troposphere between 1.5 and 2.0 K and 1.5 and 2.5 g kg^-1. HAMSR’s relative humidity error STD increases from approximately 10% in the lower troposphere to 30% in the upper troposphere. The 3CH method error estimates are generally consistent with prior independent estimates of errors and uncertainties for the HAMSR and dropsonde data sets, although they are somewhat larger, likely due to the inclusion of representativeness errors (differences associated with different spatial and temporal scales represented by the data).

The ensemble Kalman Filter (EnKF) and the 4D variational method (4DVar) are the most commonly used filters and smoothers in atmospheric science. These methods typically approximate prior densities using a Gaussian and solve a linear system of equations for the posterior mean and covariance. Therefore, strongly nonlinear model dynamics and measurement operators can lead to bias in posterior estimates. To improve the performance in nonlinear regimes, minimization of the 4DVar cost function typically follows multiple sets of iterations, known as an “outer loop”, which helps reduce bias caused by linear assumptions. Alternatively, “iterative ensemble methods” follow a similar strategy of periodically re-linearizing model and measurement operators. These methods come with different, possibly more appropriate, assumptions for drawing samples from the posterior density, but have seen little attention in numerical weather prediction (NWP) communities. Lastly, particle filters (PFs) present a purely Bayesian filtering approach for state estimation, which avoids many of the assumptions made by the above methods. Several strategies for applying localized PFs for NWP have been proposed very recently. The current study investigates intrinsic limitations of current data assimilation methodology for applications that require nonlinear measurement operators. In doing so, it targets a specific problem that is relevant to the assimilation of remotely-sensed measurements, such as radar reflectivity and all-sky radiances, which pose challenges for Gaussian-based data assimilation systems. This comparison includes multiple data assimilation approaches designed recently for nonlinear/non-Gaussian applications, as well as those currently used for NWP.

Hurricane Michael formed on October 7, 2018, in the Northwestern Caribbean Sea, and quickly traveled northward through the Gulf of Mexico, making landfall on the Florida panhandle as a devastating Category 5 hurricane only 3 days later. Before landfall, Michael underwent rapid intensification, despite unfavorable atmospheric conditions. Using observations, we characterized the key ocean features encountered by Michael along its track, which are known for favoring hurricane intensification: high sea surface temperatures, upper ocean heat content and low salinity barrier layer conditions. Ocean observations were consistent with suppressed hurricane-induced upper ocean cooling, which could only be observed by underwater gliders, and showed that Hurricane Michael constantly experienced sea surface temperatures above 28°C. We carried out ocean Observing System Experiments, which demonstrate that the combined assimilation of in situ and satellite ocean observations into a numerical ocean model led to the most realistic representation of the ocean conditions. They also suggest that, when using the Cooper-Haines (1996) method to assimilate altimetry observations, assimilating temperature observations is necessary to constrain the model upper ocean vertical structure. We also performed coupled hurricane-ocean simulations to assess the impact of ocean initial conditions on forecasting Michael. These simulations demonstrate that the ocean conditions, in particular the high sea surface temperatures north of 24°N, played a crucial role in the intensification of Michael. Coupled simulations initialized with the most realistic ocean conditions, constrained by field and satellite observations, show a ∼56% error reduction in wind intensity prior to landfall compared to simulations initialized without data assimilation.

Devastating Japan in October 2019, Supertyphoon (STY) Hagibis was an important typhoon in the history of the Pacific. A striking feature of Hagibis was its explosive rapid intensification (RI). In 24 h, Hagibis intensified by 100 kt, making it one of the fastest-intensifying typhoons ever observed. After RI, Hagibis’s intensification stalled. Using the current typhoon intensity record holder, i.e., STY Haiyan (2013), as a benchmark, this work explores the intensity evolution differences of these two high-impact STYs. We found that the extremely high pre-storm sea surface temperature reaching 30.5°C, deep/warm pre-storm ocean heat content reaching 160 kJ cm⁻², fast forward storm motion of ~8 ms⁻¹, small during-storm ocean cooling effect of ~ 0.5°C, significant thunderstorm activity at its center, and rapid eyewall contraction were all important contributors to Hagibis’s impressive intensification. There was 36% more air-sea flux for Hagibis’s RI than for Haiyan’s. After its spectacular RI, Hagibis’s intensification stopped, despite favorable environments. Haiyan, by contrast, continued to intensify, reaching its record-breaking intensity of 170 kt. A key finding here is the multiple pathways that storm size affected the intensity evolution for both typhoons. After RI, Hagibis experienced a major size expansion, becoming the largest typhoon on record in the Pacific. This size enlargement, combined with a reduction in storm translational speed, induced stronger ocean cooling that reduced ocean flux and hindered intensification. The large storm size also contributed to slower eyewall replacement cycles (ERCs), which prolonged the negative impact of the ERC on intensification.

Thermodynamic information from low levels in the atmosphere is crucial for operational weather forecasts and meteorological researchers. The NOAA Unique Combined Atmospheric Processing System (NUCAPS) sounding products have been proven beneficial to fill the data gap between synoptic radiosonde observations (RAOBs). However, compared with the upper troposphere, the accuracy of NUCAPS soundings in the low levels still needs improvement. In this study, a deep neural network (DNN) is applied to fuse multiple data sources to enhance the NUCAPS temperature and moisture profiles in the lower atmosphere. The network is developed by combining satellite observations, including NUCAPS sounding retrievals and high resolution geostationary satellite observations from the Advanced Baseline Imager, and surface analysis from the Real-Time Mesoscale Analysis (RTMA) as inputs, while collocated soundings from ECMWF re-analysis version 5 are used as the benchmark for the training. The performance of the model is evaluated by using the independent testing data set, data from a different year, as well as collocated RAOBs, showing improvement to the temperature and moisture profiles by reducing the root-mean-squared-error (RMSE) by more than 30% in the lower atmosphere (from 700 hPa to surface) in both clear sky and partially cloudy conditions. A convective event from June 18, 2017 is presented to illustrate the application of the enhanced low level soundings on high impact weather events. The enhanced soundings from fused data capture the large surface-based convective available potential energy structures in the preconvection environment, which is very useful for severe storm nowcasting and forecasting applications.

An observing system experiment (OSE) was conducted to assess the impact of wind products derived from the Cyclone Global Navigation Satellite System (CYGNSS) on tropical cyclone (TC) track, maximum 10-m wind speed (V_max), and minimum sea level pressure forecasts. The experiment used a global data assimilation and forecast system and the impact of both CYGNSS-derived scalar and vector wind retrievals was investigated. The CYGNSS-derived vector wind products were generated by optimally combining the scalar winds and a gridded a priori vector field. Additional tests investigated the impact of CYGNSS data on a regional model through the impact of lateral boundary and initial conditions from the global model during the developmental phase of Hurricane Michael (2018). In the global model, statistically significant track forecast improvements of 20-40 km were found in the first 60 h. V_max forecasts showed some significant degradations of ~2 kts at a few lead times, especially in the first 24 h. At most lead times, impacts were not statistically significant. Degradations in V_max for Hurricane Michael in the global model were largely attributable to a failure of the CYGNSS-derived scalar wind test to produce rapid intensification in the forecast failure of the CYGNSS-derived scalar wind test to produce rapid intensification in the forecast symmetrical compared to the control and CYGNSS-derived vector wind test. The regional model used initial and lateral boundary conditions from the global control and CYGNSS scalar wind tests. The regional forecasts showed large improvements in track, V_max, and minimum sea level pressure.

Limited-area numerical weather prediction models currently run operationally in the United States follow a “partially-cycled” schedule, where sequential data assimilation is periodically interrupted by replacing model states with solutions interpolated from a global model. While this strategy helps overcome several practical challenges associated with real-time regional forecasting, it is no substitute for a robust sequential data assimilation approach for research-to-operations purposes. Partial cycling can mask systematic errors in weather models, data assimilation systems, and data pre-processing techniques, since it introduces information from a different prediction system. It also adds extra heuristics to the model initialization steps outside the general Bayesian filtering framework from which data assimilation methods are derived. This study uses a research-oriented modeling system, which is self-contained in the operational Hurricane Weather Research and Forecasting (HWRF) model package, to illustrate why next-generation modeling systems should prioritize sequential data assimilation at early stages of development. This framework permits the rigorous examination of all model system components—in a manner that has never been done for the HWRF model. Examples presented in this manuscript show how sequential data assimilation capabilities can accelerate model advancements and increase academic involvement in operational forecasting systems at a time when the United States is developing a new hurricane forecasting system.

Recent (past ~15 years) advances in our understanding of tropical cyclone (TC) intensity change processes using aircraft data are summarized here. The focus covers a variety of spatiotemporal scales, regions of the TC inner core, and stages of the TC lifecycle, from preformation to major hurricane status. Topics covered include (1) characterizing TC structure and its relationship to intensity change; (2) TC intensification in vertical shear; (3) planetary boundary layer (PBL) processes and air–sea interaction; (4) upper-level warm core structure and evolution; (5) genesis and development of weak TCs; and (6) secondary eyewall formation/eyewall replacement cycles (SEF/ERC). Gaps in our airborne observational capabilities are discussed, as are new observing technologies to address these gaps and future directions for airborne TC intensity change research.

Multiple observation and analysis datasets are used to demonstrate two key features of the Atypical Rapid Intensification (ARI) process that occurred in Atlantic Hurricane Dorian (2019): (1) precession and nutations of the vortex tilt; and (2) blocking of the impinging upper-level environmental flow by the outflow. As Dorian came under the influence of an upper-level anticyclone, traditional methods of estimating vertical wind shear all indicated relatively low values were acting on the storm; however, high-spatiotemporal-resolution atmospheric motion vectors (AMVs) indicated that the environmental flow at upper levels was actually impinging on the vortex core, resulting in a vertical tilt. We employ a novel ensemble of centers of individual swaths of dual-Doppler radar data from WP-3D aircraft to characterize the precession and wobble of the vortex tilt. This tilting and wobbling preceded a sequence of outflow surges that acted to repel the impinging environmental flow, thereby reducing the shear and permitting ARI. We then apply prior methodology on satellite imagery for distinguishing ARI features. Finally, we use the AMV dataset to experiment with different shear calculations and show that the upper-level cross-vortex flow approaches zero. We discuss the implication of these results with regards to prior works on ARI and intensification in shear.

Over 50 years since Lorenz’s 1963 study and a follow-up presentation in 1972, the statement "weather is chaotic" has been well accepted. Such a view turns our attention from regularity associated with Laplace’s view of determinism to irregularity associated with chaos. In contrast to single type chaotic solutions, recent studies using a generalized Lorenz model (GLM) have focused on the coexistence of chaotic and regular solutions that appear within the same model using the same modeling configurations but different initial conditions. The results, with attractor coexistence, suggest that the entirety of weather possesses a dual nature of chaos and order with distinct predictability. In this study, based on the GLM, we illustrate the following two mechanisms that may enable or modulate two kinds of attractor coexistence and, thus, contribute to distinct predictability: (1) the aggregated negative feedback of small-scale convective processes that can produce stable non-trivial equilibrium points and, thus, enable the appearance of stable steady-state solutions and their coexistence with chaotic or nonlinear oscillatory solutions, referred to as the 1^st and 2^nd kinds of attractor coexistence; and (2) the modulation of large-scale time varying forcing (heating) that can determine (or modulate) the alternative appearance of two kinds of attractor coexistence. Based on our results, we then discuss new opportunities and challenges in predictability research with the aim of improving predictions at extended-range time scales, as well as sub-seasonal to seasonal time scales.

Helical rolls are known to play a significant role in modulating both the mean and turbulence structure of the atmospheric boundary layer in tropical cyclones. However, in-situ measurements of these rolls have been limited due to safety restrictions. This study presents analyses of data collected by an aircraft operated by the Hong Kong Observatory in Typhoon Kalmaegi (1415) and Typhoon Nida (1604). Examination of the flight-level data at ~ 600 m altitude confirmed the existence of sub-kilometer-scale rolls. These rolls were mostly observed in the outer-core region. Turbulent momentum fluxes were computed using the eddy correlation method. The averaged momentum flux of flight legs with rolls was found to be ~ 2.5 times that of legs without rolls at a similar wind speed range. This result suggests that rolls could significantly modulate turbulent transfer in the tropical cyclone boundary layer. This roll effect on turbulent fluxes should be considered in the planetary boundary layer parameterization schemes of numerical models simulating and forecasting tropical cyclones.

The thermodynamic effect of downdrafts on the boundary layer and nearby updrafts are explored in idealized simulations of category-3 and category-5 tropical cyclones (Ideal3 and Ideal5). In Ideal5, downdrafts underneath the eyewall pose no negative thermodynamic influence because of eye-eyewall mixing below 2-km altitude. Additionally, a layer of higher θ_e between 1 and 2 km altitude associated with low-level outflow that extends 40 km outward from the eyewall region creates a “thermodynamic shield” that prevents negative effects from downdrafts. In Ideal3, parcel trajectories from downdrafts directly underneath the eyewall reveal that low-θ_e air initially moves radially inward allowing for some recovery in the eye, but still enters eyewall updrafts with a mean θ_e deficit of 5.2 K. Parcels originating in low-level downdrafts often stay below 400 m for over an hour and increase their θ_e by 10-14 K, showing that air-sea enthalpy fluxes cause sufficient energetic recovery. The most thermodynamically unfavorable downdrafts occur ~5 km radially outward from an updraft and transport low-θ_e mid-tropospheric air towards the inflow layer. Here, the low-θ_e air entrains into the updraft in less than five minutes with a mean θ_e deficit of 8.2 K. In general, θ_e recovery is a function of minimum parcel altitude such that downdrafts with the most negative influence are those entrained into the top of the inflow layer. With both simulated TCs exposed to environmental vertical wind shear, this study underscores that storm structure and individual downdraft characteristics must be considered when discussing paradigms for TC intensity evolution.

The spatial and temporal variation in multiscale structures during the rapid intensification of Hurricane Michael (2018) are explored using a coupled atmospheric and oceanic dataset obtained from NOAA WP-3D and G-IV aircraft missions. During Michael’s early lifecycle, the importance of ocean structure is studied to explore how the storm intensified despite experiencing moderate vertical shear. Michael maintained a fairly symmetric precipitation distribution and resisted lateral mixing of dry environmental air into the circulation upshear. The storm also interacted with an oceanic eddy field leading to cross-storm sea surface temperature (SST) gradients of ~2.5 °C. This led to the highest enthalpy fluxes occurring left-of-shear, favoring the sustainment of updrafts into the upshear quadrants and a quick recovery from low-entropy downdraft air. Later in the lifecycle, Michael interacted with more uniform and higher SSTs that were greater than 28 °C, while vertical shear imposed asymmetries in Michael’s secondary circulation and distribution of entropy. Mid-level (~4–8 km) outflow downshear, a feature characteristic of hurricanes in shear, transported high entropy air from the eyewall region outwards. This outflow created a cap which reduced entrainment across the boundary layer top, protecting it from dry mid-tropospheric air out to large radii (i.e. > 100 km), and allowing for rapid energy increases from air-sea enthalpy fluxes. Upshear, low-level (~0.5–2 km) outflow transported high-entropy air outwards which aided boundary layer recovery from low-entropy downdraft air. This study underscores the importance of simultaneously measuring atmospheric and oceanographic parameters to understand tropical cyclone structure during rapid intensification.

This study examines the shear-relative rainfall spatial distribution of tropical cyclones (TCs) during landfall based on the 19-year (1998–2016) TRMM satellite 3B42 rainfall estimate dataset and investigates the role of upper-tropospheric troughs on the rainfall intensity and distribution after TCs make a landfall over the six basins of Atlantic (ATL), eastern and central Pacific (EPA), northwestern Pacific (NWP), northern Indian Ocean (NIO), southern Indian Ocean (SIO), and South Pacific (SPA). The results show that the wavenumber 1 perturbation can contribute ∼ 50% of the total perturbation energy of total TC rainfall. Wavenumber 1 rainfall asymmetry presents the downshear-left maxima in the deep-layer vertical wind shear between 200 and 850 hPa for all the six basins prior to making a landfall. In general, wavenumber 1 rainfall tends to decrease less if there is an interaction between TCs and upper-level troughs located at the upstream of TCs over land. The maximum TC rain rate distributions tend to be located at the downshear-left (downshear) quadrant under the high (low)-potential vorticity conditions.

Cloud microphysics significantly impact tropical cyclone precipitation. A prior polarimetric radar observational study by Wu et al. (2018) revealed the ice-phase microphysical processes as the dominant microphysics mechanisms responsible for the heavy precipitation in the outer rainband of Typhoon Nida (2016). To assess the model performance regarding microphysics, three double-moment microphysics schemes (i.e., Thompson, Morrison, and WDM6) are evaluated by performing a set of simulations of the same case. While these simulations capture the outer rainband’s general structure, microphysics in the outer rainbands are strikingly different from the observations. This discrepancy is primarily attributed to different microphysics parameterizations in these schemes, rather than the differences in large-scale environments due to cloud-environment interactions. An interesting finding in this study is that the surface rain rate or liquid water content is inversely proportional to the simulated mean raindrop sizes. The mass-weighted raindrop diameters are overestimated in the Morrison and Thompson schemes and underestimated in the WDM6 scheme, while the former two schemes produce lower liquid water content than WDM6. Compared with the observed ice water content based on a new polarimetric radar retrieval method, the ice water content above the environmental 0 °C level in all simulations is highly underestimated, especially at heights above 12 km MSL where large concentrations of small ice particles are typically prevalent. This finding suggests that the improper treatment of ice-phase processes is potentially an important error source in these microphysics schemes. Another error source identified in the WDM6 scheme is overactive warm-rain processes that produce excessive concentrations of smaller raindrops.

We present a relatively simple method to estimate tropical cyclone (TC) surface wind structure (34-, 50-and 64-kt wind radii) and intensity (maximum wind speed, MWS) from wind fields acquired from the L-band SMAP radiometer and C-band Sentinel-1A/B and RADARSAT-2 synthetic aperture radar (SAR) between 2015 and 2020. The radiometer and SAR-derived wind radii and MWS are systematically compared with the best-track estimates. The root-mean-square errors (RMSEs) of R34, R50 and R64 are 31.2, 21.8 and 17.0 n mi (1 n mi =1.852 km) for radiometer, and 21.7, 16.5 and 16.3 n mi for SAR, respectively. These error values are smaller than the averaged best-track uncertainty estimates for the three wind radii. Compared to best-track reports, the bias and RMSE for the MWS estimates are-0.2 m/s and 5.8 m/s for radiometer, and 4.4 m/s and 9.1 m/s for SAR, respectively. These results are for the wind speeds in the range of 17-80 m/s. For the two typical TCs (Lionrock and Noru) in the Northwest Pacific Ocean, our results show that a combination of the radiometer and SAR wind data acquired within a very short time interval has the potential to simultaneously obtain reasonable measurements of the wind radii and intensity parameters. Moreover, for a TC with long lifecycle, such as Typhoon Noru, we demonstrate that high-resolution and multi-temporal synergistic observations from SAR and radiometer are valuable for studying fine-scale features of the wind field and characteristics of wind asymmetry associated with intensity change, as well as the evolution of TC surface wind structure and intensity.

This study developed a morphological model for tropical cyclone (TC) wind and inflow angle asymmetry based on sea surface wind fields derived from spaceborne synthetic aperture radar (SAR) images. The model extracts the standard TC morphological information (center, intensity, and radius of the maximum wind) and decomposes the SAR-derived winds into vortex rotation winds and motion vector, making the reconstruction of the entire TC structure reliable, even in areas not mapped by SAR. The derived wind speeds and inflow angles are verified with aircraft measurements by stepped-frequency microwave radiometer and dropsondes, obtaining root-mean-square errors of 4.32 m/s and 16.04 m/s, respectively. A systematic analysis of 130 SAR TCs images, collected by RADARSAT-2 and SENTINEL-1, reveals that the model can capture the main asymmetrical TC structure. Both TC asymmetry and eye size decrease as TC intensity increases.

A statistical analysis is performed on the high-frequency (3 1/3 s) output from NOAA’s cloud-permitting, high-resolution operational Hurricane Weather Research and Forecasting (HWRF) model for all tropical cyclones (TCs) in the North Atlantic basin over a 3-year period (2017-2019). High-frequency HWRF forecasts of TC track and 10-m maximum wind speed (Vmax) exhibited large fluctuations that were not captured by traditional low-frequency (6 h) model output. Track fluctuations were inversely proportional to Vmax with average values of 6-8 km. Vmax fluctuations were as high as 20 kt in individual forecasts and were a function of maximum intensity, with a standard deviation of 5.5 kt for category 2 hurricanes and smaller fluctuations for tropical storms and major hurricanes. The radius of Vmax contracted or remained steady when TCs rapidly intensified in high-frequency HWRF forecasts, consistent with observations. Running mean windows of 3-9 h were applied at synoptic times to smooth the high-frequency HWRF output to investigate its utility to operational forecasting. Smoothed high-frequency HWRF output improved Vmax forecast skill by up to 8% and produced a more realistic distribution of 6-h intensity change when compared with low-frequency, instantaneous output. Furthermore, the high-frequency track forecast output may be useful for investigating characteristics of TC trochoidal motions.

In a tropical cyclone (TC), turbulence not only exists in the planetary boundary layer (PBL) but also can be generated above the PBL by the cloud processes in the eyewall and rainbands. It is found that the Hurricane Analysis and Forecast System (HAFS), a new multi-scale operational model for TC prediction, fails to capture the intense turbulent mixing in eyewall and rainband clouds due to a poor estimation of static stability in clouds. The problem is fixed by including the effects of multi-phase water in the stability calculation. Simulations of 21 TCs and tropical storms in the North Atlantic basin of 2016–2019 hurricane seasons totaling 118 forecast cycles show that the stability correction substantially improves HAFS's skill in predicting storm track and intensity. Analyses of HAFS's simulations of Hurricane Michael (2018) show that the positive tendency of vortex's tangential wind resulting from the radially inward transport of absolute vorticity dominates the eddy correlation tendencies induced by the model-resolved asymmetric eddies and serves as a main mechanism for the rapid intensification of Michael. The sub-grid scale (SGS) turbulent transport above the PBL in the eyewall plays a pivotal role in initiating a positive feedback among the eyewall convection, mean secondary overturning circulation, vortex acceleration via the inward transport of absolute vorticity, surface evaporation, and radial convergence of moisture in the PBL. Without the SGS transport above the PBL, the model-resolved vertical transport alone may not be sufficient in initiating the positive feedback underlying the rapid intensification of TCs.

The relationship between the Madden-Julian Oscillation (MJO) and tropical cyclone rapid intensification in the northern basins of the western hemisphere is examined. All rapid-intensification events in the north/western hemisphere and the MJO phase and amplitude are compiled from 1974 to 2015. Rapid intensification events and the MJO tend to move in tandem with each other from west to east across the hemisphere, though rapid intensification appears most likely during a neutral MJO phase. The addition of this information to an operational statistical rapid intensification forecasting scheme does not significantly improve forecasts.

The goal of this paper is to introduce a new multi-storm atmosphere/ocean coupling scheme that was implemented and tested in the Basin-Scale Hurricane Weather Research and Forecasting (HWRF-B) model. HWRF-B, an experimental model developed at the National Oceanic and Atmospheric Administration (NOAA) and supported by the Hurricane Forecast Improvement Program, is configured with multiple storm-following nested domains to produce high-resolution predictions for several tropical cyclones (TCs) within the same forecast integration. The new coupling scheme parallelizes atmosphere/ocean interactions for each nested domain in HWRF-B, and it may be applied to any atmosphere/ocean coupled system. TC forecasts from this new hydrodynamical modeling system were produced in the North Atlantic and eastern North Pacific from 2017–2019. The performance of HWRF-B was evaluated, including forecasts of TC track, intensity, structure (e.g., surface wind radii), and intensity change, and simulated sea-surface temperatures were compared with satellite observations. Median forecast skill scores showed significant improvement over the operational HWRF at most forecast lead times for track, intensity, and structure. Sea-surface temperatures cooled by 1–8 °C for the five HWRF-B case studies, demonstrating the utility of the model to study the impact of the ocean on TC intensity forecasting. These results show the value of a multi-storm modeling system and provide confidence that the multi-storm coupling scheme was implemented correctly. Future TC models within NOAA, especially the Unified Forecast System’s Hurricane Analysis and Forecast System, would benefit from the multi-storm coupling scheme whose utility and performance are demonstrated in HWRF-B here.

The hurricane boundary layer (HBL) has been observed in great detail through aircraft investigations of tropical cyclones over the open ocean, but the coastal transition of the HBL has been less frequently observed. During the landfall of Hurricane Irene (2011), research and operational aircraft over water sampled the open ocean HBL simultaneously with ground-based research and operational Doppler radars onshore. The location of the radars afforded 13 hours of dual-Doppler analysis over the coastal region. Thus, the HBL from the coastal waterways, through the coastal transition, and onshore was observed in great detail for the first time. Three regimes of HBL structure were found. The outer bands were characterized by temporal perturbations of the HBL structure with attendant low-level wind maxima in the vicinity of rainbands. The inner core, in contrast, did not produce such perturbations, but did see a reduction of the height of the maximum wind and a more jet-like HBL wind profile. In the eyewall, a tangential wind maximum was observed within the HBL over water as in past studies and above the HBL onshore. However, the transition of the tangential wind maximum through the coastal transition showed that the maximum continued to reside in the HBL through 5 km inland, which has not been observed previously. It is shown that the adjustment of the HBL to the coastal surface roughness discontinuity does not immediately mix out the residual high momentum jet aloft. Thus, communities closest to the coast are likely to experience the strongest winds onshore prior to the complete adjustment of the HBL.

A 14-member high-resolution ensemble of Edouard (2014), a moderately sheared tropical storm that underwent rapid intensification (RI), is used to determine causes of vortex alignment and precipitation symmetry prior to RI. Half the members intensify similarly to the NHC’s best track, while the other 7 ensemble members fail to reproduce intensification. Analyses of initial conditions (vertical wind shear, sea surface temperatures, relative humidity, vortex structure) reveal that lower humidity and weaker, more tilted vortices in non-intensifying members likely increase their susceptibility to boundary layer flushing episodes. As the simulations progress, vortex tilt, inner core humidity, and azimuthal variations in the structure of precipitation best differentiate the two ensemble subsets. Although all members initially are slowly intensifying asymmetric storms, the RI members are unique in that they have more persistent deep convection downshear, which favors vortex alignment via the stretching term and/or precession. As deep convection transitions to stratiform precipitation and anvil clouds in the upshear quadrants, evaporation and sublimation of condensate advected from the downshear quadrants moistens the mid-upper troposphere. This is hypothesized to promote an increase in precipitation symmetrization, a necessary precursor for RI.

Tropical Cyclone (TC) rapid intensification (RI) is difficult to predict and poses a formidable threat to coastal populations. A warm upper ocean is well-known to favor RI, but the role of ocean salinity is less clear. This study shows a strong inverse relationship between salinity and TC RI in the eastern Caribbean and western tropical Atlantic due to near-surface freshening from the Amazon-Orinoco River system. In this region, rapidly intensifying TCs induce a much stronger surface enthalpy flux compared to more weakly intensifying storms, in part due to a reduction in SST cooling caused by salinity stratification. This reduction has a noticeable positive impact on TCs undergoing RI, but the impact of salinity on more weakly intensifying storms is insignificant. These statistical results are confirmed through experiments with an ocean mixed layer model, which show that the salinity-induced reduction in SST cold wakes increases significantly as the storm’s intensification rate increases. Currently, operational statistical-dynamical RI models do not use salinity as a predictor. Through experiments with a statistical RI prediction scheme, it is found that the inclusion of surface salinity significantly improves the RI detection skill, offering promise for improved operational RI prediction. Satellite surface salinity may be valuable for this purpose, given its global coverage and availability in near real-time.

Our collective understanding of azimuthally-asymmetric features within the coherent structure of a tropical cyclone (TC) continues to improve with the availability of more detailed observations and high-resolution model outputs. However, a precise understanding of how these asymmetries impact TC intensity changes is lacking. Prior attempts at investigating the asymmetric impacts follow a mean-eddy partitioning that condenses the effect of all the asymmetries into one term and fails to highlight the differences in the role of asymmetries at different scales. In this study, we present a novel energetics-based approach to analyze the asymmetric impacts at multiple length-scales during periods of rapid intensity changes. Using model outputs of TCs under low and high shear, we compute the different energy pathways that enhance/suppress the growth of multi-scale asymmetries in the wavenumber (WN) domain. We then compare and contrast the energetics of the mean flow field (WN 0) with that of the persistent, coherent vortex-scale asymmetric structures (WNs 1,2) and the more local, transient, sub-vortex-scale asymmetries (WNs ≥ 3). We find in our case-studies that the dominant mechanisms of growth/decay of the asymmetries are the baroclinic conversion from available potential to kinetic energy at individual scales of asymmetries and the transactions of kinetic energy between the asymmetries of various length-scales, rather than the barotropic mean-eddy transactions as is typically assumed. Our case-study analysis further shows that the growth/decay of asymmetries is largely independent of the mean. Certain aspects of eddy energetics can potentially serve as early-warning indicators of TC rapid intensity changes.

The Developmental Testbed Center (DTC) tested two convective parameterization schemes in the Hurricane Weather Research and Forecasting (HWRF) model and compared them in terms of performance of forecasting tropical cyclones (TCs). Several TC forecasts were conducted with the scale aware Simplified Arakawa Schubert (SAS) and Grell-Freitas (GF) convective schemes over the Atlantic basin. For this sample of over 100 cases, the storm track and intensity forecasts were superior for the GF scheme compared to SAS. A case study showed improved storm structure for GF when compared with radar observations. The GF run had increased inflow in the boundary layer which resulted in higher angular momentum. An angular momentum budget analysis shows that the difference in the contribution of the eddy transport to the total angular momentum tendency is small between the two forecasts. The main difference is in the mean transport term, especially in the boundary layer. The temperature tendencies indicate higher contribution from the microphysics and cumulus heating above the boundary layer in the GF run. A temperature budget analysis indicated that both the temperature advection and diabatic heating were the dominant terms and they were larger near the storm center in the GF run than in the SAS run. The above results support the superior performance of the GF scheme for TC intensity forecast.

The impact of swell on wind stress is investigated through direct three‐layer flux measurements taken by a fixed tower in the marine atmospheric boundary layer. Observations confirm that the assumption of constant momentum flux layer is valid under swell‐dominated conditions around the reference height of 10 m. The swell can modulate the total wind stress to be less than the turbulent stress derived from the first‐order closure method, and the extent of this modulation decreases with height. The critical layer that represents the top of the layer affected by stronger swells is estimated to reach 45‐m altitude, and the depth of this layer decreases as the swells weaken and the wind speed increases. Furthermore, a simple swell correction scheme for the total stress calculation is developed, showing good performance against observations.

Unique near-surface observations were collected in hurricanes using a small unmanned aircraft system deployed from NOAA’s hurricane hunter aircraft. Unique data from seven flights of the Coyote small Unmanned Aircraft System (sUAS) were collected in Hurricanes Maria (2017) and Michael (2018). Using NOAA's P-3 reconnaissance aircraft as a deployment vehicle, the sUAS collected high-frequency (> 1 Hz) measurements in the turbulent boundary layer of hurricane eyewalls, including measurements of wind speed, wind direction, pressure, temperature, moisture, and sea surface temperature, which are valuable for advancing knowledge of hurricane structure and the process of hurricane intensification. This study presents an overview of the sUAS system and preliminary analyses that were enabled by these unique data. Among the most notable results are measurements of turbulence kinetic energy and momentum flux for the first time at low levels (< 150 m) in a hurricane eyewall. At higher altitudes and lower wind speeds, where data were collected from previous flights of the NOAA P-3, the Coyote sUAS momentum flux values are encouragingly similar, thus demonstrating the ability of an sUAS to measure important turbulence properties in hurricane boundary layers. Analyses from a large-eddy simulation (LES) are also used to place the Coyote measurements into context of the complicated high-wind eyewall region. Thermodynamic data are also used to evaluate the operational HWRF model, showing a cool, dry, and thermodynamically unstable bias near the surface. Preliminary data assimilation experiments also show how sUAS data can be used to improve analyses of storm structure. These results highlight the potential of sUAS operations in hurricanes, and suggest opportunities for future work using these promising new observing platforms.

Observing System Simulation Experiments (OSSEs) were conducted to evaluate the potential impact of the six Global Navigation Satellite System (GNSS) radio occultation (RO) receiver satellites in equatorial orbit from the initially proposed Constellation Observing Satellites for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) mission, known as COSMIC-2A. Furthermore, the added value of the high-inclination component of the proposed mission was investigated by considering a few alternatives architecture designs, including the originally proposed polar constellation of six satellites (COSMIC-2B), a constellation with a reduced number of RO receiving satellites, and a constellation of six satellites but with fewer observations in the lower troposphere. The 2015-year version of the operational three-dimensional ensemble-variational data assimilation system of the National Centers for Environment Prediction (NCEP)’s was used to run the OSSEs. Observations were simulated and assimilated using the same methodology and their errors assumed uncorrelated. The largest benefit from the assimilation of COSMIC-2A, with denser equatorial coverage, was to improve tropical winds, and its impact was found overall neutral in the extratropics. When soundings from the high-inclination orbit were assimilated in addition to COSMIC-2A, positive benefits were found globally, confirming that a high-inclination orbit constellation of RO receiving satellites is necessary to improve weather forecast skill globally. The largest impact from reducing COSMIC-2B from six to four satellites was to slightly degrade weather forecast skill in the northern hemisphere extratropics. The impact of degrading COSMIC-2B to COSMIC level of accuracy, in terms of penetration into the lower troposphere, was mostly neutral.

For the last six years, the Florida Reef Tract (FRT) has been experiencing an outbreak of the Stony Coral Tissue Loss Disease (SCTLD). First reported off the coast of Miami-Dade County in 2014, the SCTLD has since spread throughout the entire FRT with the exception of the Dry Tortugas. However, the causative agent for this outbreak is currently unknown. Here we show how a high-resolution bio-physical model coupled with a modified patch Susceptible-Infectious-Removed epidemic model can characterize the potential causative agent(s) of the disease and its vector. In the present study, the agent is assumed to be transported within composite material (e.g., coral mucus, dying tissues, and/or resuspended sediments) driven by currents and potentially persisting in the water column for extended periods of time. In this framework, our simulations suggest that the SCTLD is likely to be propagated within neutrally buoyant material driven by mean barotropic currents. Calibration of our model parameters with field data shows that corals are diseased within a mean transmission time of 6.45 days, with a basic reproduction number slightly above 1. Furthermore, the propagation speed of the disease through the FRT is shown to occur for a well-defined range of values of a disease threshold, defined as the fraction of diseased corals that causes an exponential growth of the disease in the reef site. Our results present a new connectivity-based approach to understand the spread of the SCTLD through the FRT. Such a method can provide a valuable complement to field observations and lab experiments to support the management of the epidemic as well as the identification of its causative agent.

The next generation Hurricane Analysis and Forecast System (HAFS) has been developed recently in the National Oceanic and Atmospheric Administration (NOAA) to accelerate the improvement of tropical cyclone (TC) forecasts within the Unified Forecast System (UFS) framework. The finite-volume cubed sphere (FV3) based convection-allowing HAFS Stand-Alone Regional model (HAFS-SAR) was successfully implemented during Hurricane Forecast Improvement Project (HFIP) real-time experiments for the 2019 Atlantic TC season. HAFS-SAR has a single large 3-km horizontal resolution regional domain covering the North Atlantic basin. A total of 273 cases during the 2019 TC season are systematically evaluated against the best track and compared with three operational forecasting systems: Global Forecast System (GFS), Hurricane Weather Research and Forecasting model (HWRF), and Hurricanes in a Multi-scale Ocean-coupled Non-hydrostatic model (HMON). HAFS-SAR has the best performance in track forecasts among the models presented in this study. The intensity forecasts are improved over GFS, but show less skill compared to HWRF and HMON. The radius of gale force wind is over-predicted in HAFS-SAR, while the hurricane force wind radius has lower error than other models.

Under extreme weather conditions, the imprints of kilometer-scale marine atmospheric boundary layer roll vortices on the ocean surface are clearly visible in synthetic aperture radar (SAR) images of storms. Therefore, information about wind direction in storms can be obtained by analyzing SAR image features caused by boundary layer rolls. VH-polarized SAR imagery captures the structural features of storms well and shows prominent image gradients along the radial directions of the storm. The signal-to-noise ratios of VH-polarized images are small in low wind speed areas, but they are large in the same regions of VV-polarized images. The capability of retrieving the atmospheric rolls orientation in VV-polarization is also found to be sensitive to incidence angle, with better performances for larger incidence angles. Thus, there is the potential to retrieve the storm’s wind directions using a combination of the VH- and VV-polarized SAR observations. In this article, we use the local gradient method to estimate tropical cyclone (TC) wind directions from C-band RADARSAT-2 and Sentinel-1A dual-polarization (VV + VH) SAR imagery. As a case study, wind directions with a spatial resolution of 25 km are derived by using both wide-swath VV- and VH-polarized SAR imagery over two hurricanes (Earl and Bertha) and one typhoon (Meranti). We compare wind directions derived from ten dual-polarization SAR images with collocated wind directions from buoys, Global Positioning System (GPS) dropsondes, a scatterometer, and a radiometer. Statistical comparisons show that the wind direction bias and root-mean-square error are, respectively, -0.54° and 14.78° for VV-polarization, 0.38° and 14.25° for VH-polarization, 0.20° and 13.30° for VV- and VH-polarization, suggesting dual-polarization SAR is more suitable for the estimation of TC wind directions than VV- or VH-polarization SAR.

The local particle filter (LPF) and the local nonlinear ensemble transform filter (LNETF) are two moment-matching nonlinear filters to approximate the classical particle filter (PF). They adopt different strategies to alleviate filter degeneracy. LPF and LNETF localize observational impact but use different localization functions. They assimilate observations in a partially sequential and a simultaneous manner, respectively. In addition, LPF applies the resampling step, whereas LNETF applies the deterministic square root transformation to update particles. Both methods preserve the posterior mean and variance of the PF. LNETF additionally preserves the posterior correlation of the PF for state variables within a local volume. These differences lead to their differing performance in filter stability and posterior moment estimation. LPF and LNETF are systematically compared and analyzed here through a set of experiments with a Lorenz model. Strategies to improve the LNETF are proposed. The original LNETF is inferior to the original LPF in filter stability and analysis accuracy, particularly for small particle numbers. This is attributed to both the localization function and particle update differences. The LNETF localization function imposes a stronger observation impact than the LPF for remote grids and thus is more susceptible to filter degeneracy. The LNETF update causes an overall narrower range of posteriors that excludes true states more frequently. After applying the same localization function as the LPF and additional posterior inflation to the LNETF, the two filters reach similar filter stability and analysis accuracy for all particle numbers. The improved LNETF shows more accurate posterior probability distribution but slightly worse spatial correlation of posteriors than the LPF.

The initiation of a rapid intensification (RI) event for a tropical cyclone (TC) at major hurricane intensity is a rare event in the North Atlantic basin. This study examined the environmental and vortex-scale processes related to such an RI event observed in Hurricane Irma (2017) using a combination of flight-level and airborne radar aircraft reconnaissance observations, microwave satellite observations, and model environmental analyses. The onset of RI was linked to an increase in sea surface temperatures and ocean heat content toward levels more commonly associated with North Atlantic RI episodes. Remarkably, Irma’s RI event was comprised of two rapidly-evolving eyewall replacement cycle (ERC) episodes that each completed in less than 12 h. The two ERC events displayed different secondary eyewall formation (SEF) mechanisms and vortex evolutions. During the first SEF event, a secondary maximum in ascent and tangential wind was observed at the leading edge of a mesoscale descending inflow jet. During the ensuing ERC event, the primary eyewall weakened and ultimately collapsed, resulting in a brief period of weakening. The second SEF event displayed characteristics consistent with unbalanced boundary layer dynamics. Additionally, it is plausible both SEF events were affected by the stagnation and axisymmeterization of outward propagating vortex Rossby waves. During the second ERC event, the TC continued to rapidly intensify, which is a stark contrast to the ERC paradigm described in the literature. The differing ERC evolutions appear linked to the vortex response to changing environmental conditions. The results presented here underscore the utility of frequent aircraft reconnaissance observations for an improved understanding of TC dynamics.

This technical report describes the activities and results of the Hurricane Forecast Improvement Program (HFIP) that occurred in 2019. The major development focus in 2019 was on building the next generation hurricane model—the Hurricane Analysis and Forecast System (HAFS)—primarily for track and intensity predictions. This report summarizes the progress in 2019, including model developments and the first year of progress made towards transforming it into the next generation of HFIP.

The structure of vortex Rossby waves (VRWs) and their role in the development of a secondary eyewall in Hurricane Matthew (2016) is examined from observations taken during the NOAA Sensing Hazards with Operational Unmanned Technology (SHOUT) field experiment. Radar measurements from ground-based and airborne systems, with a focus on the NASA High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) instrument on the Global Hawk aircraft, revealed the presence of ~12–15-km wavelength spiral bands breaking from the inner core eyewall in the down shear-right quadrant. The vorticity characteristics and calculations of the intrinsic phase speeds of the bands are shown to be consistent with sheared VRWs. A new angular momentum budget methodology is presented that allows an understanding of the secondary eyewall development process with narrow swath radar measurements. Filtering of the governing equations enables explicit insight into the nonlinear dynamics of scale interactions and the role of the VRWs in the storm structure change. The results indicate that the large-scale (scales>15-km) vertical flux convergence of angular momentum associated with the VRWs dominates the time tendency with smaller effects from the radial flux term. The small-scale (scales≤15-km) vertical term produces weak, but non-negligible nonlinear forcing of the large scales primarily through the Reynolds and cross-stress components. The projection of the wave kinematics onto the low-wavenumber (zero and one) fields appears to be the more significant dynamic process. Flight-level observations show secondary peaks in tangential winds in the radial region where the VRW forcing signatures are active, connecting them with the secondary eyewall formation process.

We present the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), an atmosphere model developed by the Geophysical Fluid Dynamics Laboratory (GFDL) coupling the nonhydrostatic FV3 Dynamical Core to a physics suite originally taken from the Global Forecast System. SHiELD is designed to demonstrate new capabilities within its components, explore new model applications, and to answer scientific questions through these new functionalities. A variety of configurations are presented, including short‐to‐medium‐range and subseasonal‐to‐seasonal prediction, global‐to‐regional convective‐scale hurricane and contiguous U.S. precipitation forecasts, and global cloud‐resolving modeling. Advances within SHiELD can be seamlessly transitioned into other Unified Forecast System or FV3‐based models, including operational implementations of the Unified Forecast System. Continued development of SHiELD has shown improvement upon existing models. The flagship 13‐km SHiELD demonstrates steadily improved large‐scale prediction skill and precipitation prediction skill. SHiELD and the coarser‐resolution S‐SHiELD demonstrate a superior diurnal cycle compared to existing climate models; the latter also demonstrates 28 days of useful prediction skill for the Madden‐Julian Oscillation. The global‐to‐regional nested configurations T‐SHiELD (tropical Atlantic) and C‐SHiELD (contiguous United States) show significant improvement in hurricane structure from a new tracer advection scheme and promise for medium‐range prediction of convective storms.

The FV3GFS is the current operational Global Forecast System (GFS) at the National Centers for Environmental Prediction (NCEP), which combines a finite volume cubed sphere dynamical core (i.e. abbreviated as FV3) and GFS physics. In this study, FV3GFS is used to gain understanding of rapid intensification (RI) of tropical cyclones (TCs) in shear. The analysis demonstrates the importance of TC structure in a complex system like Hurricane Michael, which intensified to a Category 5 hurricane over the Gulf of Mexico despite over 20 kt (10 m s^-1) of vertical wind shear. Michael’s RI is examined using a global-nest FV3GFS ensemble with the nest at 3-km resolution. The ensemble shows a range of peak intensities from 77 to 159 kt (40 to 82 m s^-1). Precipitation symmetry, vortex tilt, moisture, and other aspects of Michael’s evolution are compared through composites of stronger and weaker members. The 850–200 hPa vertical shear is 22 kt (11 m s^-1) in the mean of both strong and weak members during the early stage. Tilt and moisture are two distinguishing factors between strong and weak members. The relationship between vortex tilt and humidification is complex, and other studies have shown both are important for sheared intensification. Here, it is shown that tilt reduction leads to upshear humidification and is thus a driving factor for intensification. A stronger initial vortex and early evolution of the vortex also appear to be the key to members that are able to resist the sheared environment.

The role of elevated sea temperatures in coral bleaching has been well documented. Many of the sea temperature records utilized for purposes of widespread, multi-species bleaching predictions in recent publications have been acquired through satellite remote sensing. Satellites estimate sea temperatures at only a narrow range of depths near the surface of the ocean and may, therefore, not adequately represent the true temperatures endured by the world’s coral ecosystems. To better characterize sea temperature regimes that coral reef ecosystems experience, as well as better define the individual thresholds for each species that bleaches, in situ sea temperature sensors are required. Commercial sensors are expensive in large quantities, however, reducing the capacity to conduct large-scale research programs to elucidate the range of significant scales of temperature variability. At the National Oceanic and Atmospheric Administration’s (NOAA) Atlantic Oceanographic and Meteorological Laboratory (AOML), we designed a low-cost (roughly US $9 in parts) and high-precision sea temperature sensor that uses an Arduino microprocessor board and a high accuracy thermistor. This new temperature sensor autonomously records temperatures onto a memory chip and provides better accuracy (+0.05°C) than a comparable commercial sensor (+0.2°C). Moreover, it is not difficult to build—anyone who knows how to solder can build the temperature sensor. In March 2019, students at middle and high schools in Broward County, Florida built close to 60 temperature sensors. During 2019, these sensors will be deployed by Reef Check, a global-scale coral reef monitoring organization, as well as by other programs, to determine worldwide sea temperature regimes through the Opuhala Project (https://www.coral.noaa.gov/opuhala). This paper chronicles results from the initial proof-of-concept deployments for these AOML-designed sensors.

The JPL Tropical Cyclone Information System integrates observations with model forecasts, allowing interrogation of a large number of variables, to help better understand the multi-scale non-linear interactions that lead to storm development, and to evaluate models. Tropical cyclones (TCs) are among the most destructive natural phenomena with huge societal and economic impact. They form and evolve as the result of complex multi-scale processes and non-linear interactions. Even today the understanding and modeling of these processes is still lacking. A major goal of NASA is to bring the wealth of satellite and airborne observations to bear on addressing the unresolved scientific questions and improving our forecast models. Despite their significant amount, these observations are still underutilized in hurricane research and operations, due to the complexity associated with finding and bringing together semi-coincident and semi-contemporaneous multi-parameter data that are needed to describe the multiscale TC processes. Such data are traditionally archived in different formats, with different spatio-temporal resolution, across multiple databases, and hosted by various agencies. To address this shortcoming, NASA supported the development of the Jet Propulsion Laboratory (JPL) Tropical Cyclone Information System (TCIS) - a Data Analytic Framework that integrates model forecasts with multiparameter satellite and airborne observations, providing interactive visualization and on-line analysis tools. TCIS supports interrogation of a large number of atmospheric and ocean variables, allowing for quick investigation of the structure of the tropical storms and their environments. This paper provides an overview of the TCIS’s components and features. It also summarizes recent pilot studies, providing examples how the TCIS has inspired new research, helping to increase our understanding of TCs. The goal is to encourage more users to take full advantage of the novel capabilities. TCIS allows atmospheric scientists to focus on new ideas and concepts rather than painstakingly gathering data scattered over several agencies.

Starting in 2011, coastal areas of the Caribbean Sea and tropical Atlantic Ocean began to experience extraordinary yearly accumulations of pelagic Sargassum brown alga. Historical reports place large quantities of Sargassum only in the North Atlantic (mostly in the Gulf of Mexico and the Sargasso Sea). Accumulations of Sargassum in the tropical Atlantic have continued. We used a numerical particle-tracking system, wind and current reanalysis data, drifting buoy trajectories, and satellite imagery to determine the origin of the Sargassum that is now found persistently in the tropical Atlantic. Our analyses suggest that during the extreme negative phase of the winter 2009-2010 North Atlantic Oscillation (NAO), unusually strong and southward-shifted westerly winds explain the transport of Sargassum from the Sargasso Sea (∼20-40°N, 80-20°W) into the far eastern North Atlantic. Our hindcast Sargassum distributions agree with surface current simulations with the inclusion of “windage”. Windage is the additional, wind-induced drift of material floating at the free surface resulting from direct wind forcing on the sea surface, as well as on floating or partially-submerged objects. In our simulations, windage is included as an added vector (speed and direction) to the model-computed surface ocean currents equivalent to 1% of surface wind velocities. Lagrangian analysis of the regional circulation suggests that (1) part of the Sargassum subsequently drifted to the southwest in the North Equatorial Current (NEC) and entered the central tropical Atlantic, arriving in the Caribbean by the spring of 2011, with (2) another portion continuing southward along the coast of Africa in the Canary Current, eventually joining the seasonally-varying system of tropical Atlantic currents and thereby delivering a large Sargassum population to the tropical Atlantic. Since then, Sargassum patches aggregate from March to September in massive windrows along the Inter-Tropical Convergence Zone (ITCZ) under the action of converging winds. The windrows follow the ITCZ in its seasonal northward migration in the central tropical Atlantic. They are stretched across the central tropical Atlantic as the ITCZ crosses the latitude of the seasonal formation of the North Equatorial Counter Current (NECC). These patches and windrows are exposed to high sunlight and open-ocean upward flux of nutrients due to eddy and wind-driven mixing in the central tropical Atlantic. During the northern spring and summer, as the Sargassum drifts farther north with the ITCZ, large portions of the population are advected into the eastern Caribbean Sea. Some of these patches remain dispersed as the ITCZ migrates southward, and re-aggregate into new windrows as the ITCZ intensifies the following March-April. If wind mixing is strong and the mixed layer is deeper than about 50-60 m in the southern tropical Atlantic at this time, the Sargassum will bloom and form a massive windrow. Otherwise, the bloom will be inhibited. The extreme 2009-2010 NAO wind anomaly could be considered as triggering a biosphere “tipping point” that caused important ocean-scale ecosystem changes in the tropical Atlantic, with significant recurrent social and economic consequences. Understanding whether this new expanded geographic range of massive Sargassum blooms is temporary or whether it will revert to its pre-2009 distribution requires sustained monitoring and research.

Rainfall forecast performance was evaluated for the first time for the Hurricane Weather Research and Forecasting (HWRF) model. This study focused on HWRF performance in predicting rainfall from Hurricane Harvey in 2017. In particular, two configurations of the 2017 version of HWRF were investigated: a deterministic version of the Basin-scale HWRF (HB17) and an ensemble version of the operational HWRF (H17E). This study found that HB17 generated reasonable rainfall patterns and rain-rate distributions for Hurricane Harvey, in part due to accurate track forecasts. However, the estimated rain rates near the storm center (within 50 km) were slightly overestimated. In the rainband region (150 to 300 km), HB17 reproduced heavy rain rates and underestimated light rain rates. The accumulated rainfall pattern successfully captured Harvey’s intense outer rainband with adequate spatial displacement. In addition, the performance of H17E on probabilistic rainfall has shown that the ensemble forecasts can potentially increase the accuracy of the predicted locations for extreme rainfall. Moreover, the study also indicated the importance of high-resolution dynamical models for rainfall predictions. Although statistical models can generate the overall rainfall patterns along a track, extreme rainfall events produced from outer rainbands can only be forecasted by numerical models, such as HWRF. Accordingly, the HWRF models have the capability of simulating reasonable quantitative precipitation forecasts and providing essential rainfall guidance in order to further reduce loss of life and cost to the economy. here.

Few studies have examined the forecast uncertainties brought about from varying aircraft flight track patterns in targeted observations for extratropical winter storms. To examine the degree of uncertainty in downstream forecasts caused by different aircraft flight patterns, a series of observing system simulation experiments (OSSEs) are performed and demonstrated for two extratropical winter storms identified in the European Centre for Medium‐Range Weather Forecasts (ECMWF) T511 Nature Run using the National Centers for Environmental Prediction Global Data Assimilation System and Global Forecast System (Q1FY15). Winter storms were chosen to support operational Pacific Ocean targeting strategies using unmanned aircraft. For these two storms, objective and composite flight tracks are generated as they could occur in an operational field mission to sample sensitive areas and meteorologically important regions, and then the changes in downstream forecasts across the various flight tracks are evaluated. The forecast impact downstream is sensitive to flight track orientation and shows case‐dependent results, with some flight patterns leading to significant improvements, while others result in neutral to degraded forecasts. The degree of downstream uncertainty in the verification region can vary up to 8% from the different flight paths, depending on the metric used and the atmospheric variables analysed. Although the study is a demonstration of the technique and is limited to only two case studies, it suggests that uncertainty in flight path design should not be neglected in future field missions. Some guidance for mitigating this uncertainty is also discussed.

Ice microphysics observations collected from eight flights into tropical cyclones (TCs) were analyzed to examine the performance of exponential versus gamma functions in representing the particle size distributions (PSDs) for cloud ice, snow, and graupel. Eighty‐four percent (87%) of cloud ice (snow) PSDs are above the correlation threshold of 0.9 between observations and the corresponding fitted curves by gamma fits, while only 43% (55%) of cloud ice (snow) PSDs by exponential fits. Sixteen percent of graupel PSDs are above the threshold by gamma fits but none by exponential fits. The intercept, slope, and shape in gamma functions are mutually dependent. When one among the three parameters is prescribed, the other two can be empirically rendered from the mutual‐dependence relationship. Counterintuitively, temperature does not play a conspicuous role in controlling ice PSDs in the TC environment but horizontal winds do, especially for snow, through the breakup process.

Observations of dynamical information in the upper levels of tropical cyclones at high spatiotemporal resolutions are rare but very important to the analysis and prediction of the storm evolution and landfall impacts. These observations are now becoming routinely available from the new generation of geostationary weather satellites. Understanding and optimizing the utilization of that information in numerical weather prediction models is a vital step toward simulating tropical cyclone behavior and improving forecasts. The Advanced Baseline Imager (ABI) onboard GOES‐16 is providing high spatial and temporal resolution images that can be targeted on North Atlantic tropical cyclones. In addition to a full‐disk scan every 10 min and a CONUS scan every 5 min, the ABI also has a flexible “mesoscale scan” mode featuring limited moving domains at 1‐min intervals. The mesosector can focus on a targeted storm center with a 10°×10° domain coverage that follows the storm movement. Using this 1‐min ABI imagery to track cloud motions, automated algorithms have been developed to produce enhanced, high‐resolution atmospheric motion vectors (AMVs) during a targeted tropical cyclone event. These high spatiotemporal AMVs represent estimates of the wind field around the storm and can provide critical dynamical information on the targeted storm and its near environment. This information can help improve the representation of the initialized vortex in numerical model analyses. To study the impact of the enhanced AMV observations on numerical weather prediction, the Hurricane Weather Research Forecast (HWRF) model is used in a series of assimilation and forecast experiments. Three destructive Atlantic hurricane cases from 2017, Harvey, Irma, and Maria, are chosen as case studies. The results show that the assimilation of the enhanced AMVs from GOES‐16 consistently improves the HWRF hurricane track and size forecasts, and have mixed impacts on intensity forecasts. These results augment previously published studies on optimizing the quantitative use of new generation geostationary satellite rapid‐scan observations for improving high impact weather forecasts.

This paper describes the vortex initialization (VI) currently used in NCEP operational hurricane models (HWRF and HMON, and possibly HAFS in the future). The VI corrects the background fields for hurricane models: it consists of vortex relocation, and size and intensity corrections. The VI creates an improved background field for the data assimilation and thereby produces an improved analysis for the operational hurricane forecast. The background field after VI can be used as an initial field (as in the HMON model, without data assimilation) or a background field for data assimilation (as in HWRF model).

A novel Bayesian Monte Carlo Integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small scale variability of precipitation and clouds compared with the instrument footprint and also the non-linear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model are discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include, the resolution of the model (about 25 km) which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast and also the data assimilation system not being able to consider vertically correlated observation errors.

A global Observing System Simulation Experiment (OSSE) was used to assess the potential impact of a proposed Global Navigation Satellite System (GNSS) radio occultation (RO) constellation on tropical cyclone (TC) track, maximum 10-m wind speed (V_max), and integrated kinetic energy (IKE) forecasts. The OSSE system was based on the 7-km NASA nature run and simulated RO refractivity determined by the spatial distribution of observations from the original planned (i.e., including both equatorial and polar orbits) Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2). Data was assimilated using the NOAA operational weather analysis and forecasting system. Three experiments generated global TC track, V_max, and IKE forecasts over 6 weeks of the North Atlantic hurricane season in the North Atlantic, East Pacific, and West Pacific basins. Confidence in our results was bolstered because track forecast errors were similar to those of official National Hurricane Center forecasts, and V_max errors and IKE errors showed similar results. GNSS-RO assimilation did not significantly impact global track forecasts, but did slightly degrade V_max and IKE forecasts in the first 30-60 h of lead time. Global forecast error statistics show adding or excluding explicit random errors to RO profiles made little difference to forecasts. There was large forecast–to–forecast variability in RO impact. For two cases studied in depth, track and V_max improvements and degradations were traced backwards through the previous 24 h of assimilation cycles. The largest V_max degradation was traced to particularly good control analyses rather than poor analyses caused by GNSS-RO.

The provision of essential supplies is a key service provided by retailers when demand spikes due to consumer stockpiling during environmental emergencies. Moreover, it is important for retailers to quickly recover from these events by replenishing the stock of essential supplies to meet the continuing needs of local residents. The main purpose of this research is to study consumer precautionary stockpiling behavior prior to the onset of hurricane landfalls and determine the impact of this behavior on in‐store product availability for various formats of retail store outlets. Specifically, we focus on the bottled water product category, an essential emergency category in hurricane preparedness. This study combines an event analysis methodology with econometric models using archival retail scanner data from 60 US retail chains located in 963 counties and real‐time data from four recent US continental hurricanes. We find that supply‐side characteristics (retail network and product variety), demand‐side characteristics (hurricane experience and household income), and disaster characteristics (hazard proximity and hazard intensity) significantly affect consumer stockpiling propensity as the hurricanes approach. The increased consumer stockpiling has immediate and longer‐term impacts on retail operations, namely, in‐store product availability. Among various retail formats, drug stores are associated with the highest consumer stockpiling propensity before hurricanes, while dollar stores and discount stores are associated with the lowest in‐store product availability following hurricanes. Our study points to the need for retailers and policymakers to carefully monitor factors affecting consumer stockpiling behavior that will allow for better allocation of critical supplies during the hurricane season.

Our collective understanding of azimuthally asymmetric features within the coherent structure of a tropical cyclone (TC) continues to improve with the availability of more detailed observations and high-resolution model outputs. However, a precise understanding of how these asymmetries impact TC intensity changes is lacking. Prior attempts at investigating the asymmetric impacts follow a mean–eddy partitioning that condenses the effect of all the asymmetries into one term and fails to highlight the differences in the role of asymmetries at different scales. In this study, we present a novel energetics-based approach to analyze the asymmetric impacts at multiple length scales during periods of rapid intensity changes. Using model outputs of TCs under low and high shear, we compute the different energy pathways that enhance/suppress the growth of multiscale asymmetries in the wavenumber (WN) domain. We then compare and contrast the energetics of the mean-flow field (WN 0) with that of the persistent, coherent vortex-scale asymmetric structures (WNs 1 and 2) and the more local, transient, sub-vortex-scale asymmetries (WNs ≥ 3). We find in our case studies that the dominant mechanisms of growth/decay of the asymmetries are the baroclinic conversion from available potential to kinetic energy at individual scales of asymmetries and the transactions of kinetic energy between the asymmetries of various length scales, rather than the barotropic mean–eddy transactions as is typically assumed. Our case study analysis further shows that the growth/decay of asymmetries is largely independent of the mean. Certain aspects of eddy energetics can potentially serve as early-warning indicators of TC rapid intensity changes.

This study analyses Global Positioning System dropsondes to document the axisymmetric tropical cyclone (TC) boundary-layer structure, based on storm intensity. A total of 2608 dropsondes from 42 named TCs in the Atlantic basin from 1998 to 2017 are used in the composite analyses. The results show that the axisymmetric inflow layer depth, the height of maximum tangential wind speed, and the thermodynamic mixed layer depth are all shallower in more intense TCs. The results also show that more intense TCs tend to have a deep layer of the near-saturated air inside the radius of maximum wind speed (RMW). The magnitude of the radial gradient of equivalent potential temperature (θ_e) near the RMW correlates positively with storm intensity. Above the inflow layer, composite structures of TCs with different intensities all possess a ring of anomalously cool temperatures surrounding the warm-core, with the magnitude of the warm-core anomaly proportional to TC intensity. The boundary layer composites presented here provide a climatology of how axisymmetric TC boundary layer structure changes with intensity.

The mechanisms underlying the development of a deep, aligned vortex, and the role of convection and vertical shear in this process, are explored by examining airborne Doppler radarand deep layer dropsonde observations of the intensification of Hurricane Hermine (2016), a long-lived tropical depression that intensified to hurricane strength in the presence of moderate vertical wind shear. During Hermine’s intensification the low-level circulation appeared to shift toward locations of deep convection that occurred primarily downshear. Hermine began to steadily intensify once a compact low-level vortex developed within a region of deep convection in close proximity to a midlevel circulation, causing vorticity to amplify in the lower troposphere primarily through stretching and tilting from the deep convection. A notable transition of the vertical mass flux profile downshear of the low-level vortex to a bottom-heavy profile also occurred at this time. The transition in the mass flux profile was associated with more widespread moderate convection and a change in the structure of the deep convection to a bottom-heavy mass flux profile, resulting in greater stretching of vorticity in the lower troposphere of the downshear environment. These structural changes in the convection were related to a moistening in the middle troposphere downshear, a stabilization in the lower troposphere, and the development of a mid- to upper-level warm anomaly associated with the developing midlevel circulation. The evolution of precipitation structure shown here suggests a multiscale cooperative interaction across the convective and mesoscale that facilitates an aligned vortex that persists beyond convective time scales, allowing Hermine to steadily intensify to hurricane strength.

Vertical profiles of temperature, relative humidity, cloud particle concentration, median mass dimension, and mass content were derived using instruments on the NOAA P-3 aircraft for 37 spiral ascents/descents flown within five mesoscale convective systems (MCSs) during the 2015 Plains Elevated Convection at Night (PECAN) project, and 16 spiral descents of the NOAA P-3 within 10 MCSs during the 2003 Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX). The statistical distribution of thermodynamic and microphysical properties within these spirals is presented in context of three primary MCS regions—the transition zone (TZ), enhanced stratiform rain region (ESR), and the anvil region (AR)—allowing deductions concerning the relative importance and nature of microphysical processes in each region. Aggregation was ubiquitous across all MCS zones at subfreezing temperatures, where the degree of ambient subsaturation, if present, moderated the effectiveness of this process via sublimation. The predominately ice-supersaturated ESR experienced the least impact of sublimation on microphysical characteristics relative to the TZ and AR. Aggregation was most limited by sublimation in the ice-subsaturated AR, where total particle number and mass concentrations decreased most rapidly with increasing temperature. Sublimation cooling at the surface of ice particles in the TZ, the driest of the three regions, allowed ice to survive to temperatures as high as +6.8°C. Two spirals executed behind a frontal squall line exhibited a high incidence of pristine ice crystals, and notably different characteristics from most other spirals. Gradual meso- to synoptic scale ascent in this region likely contributed to the observed differences.

This study assesses where tropical cyclone (TC) surface winds can be measured as a function of footprint sizes and wavelengths (Ka- Ku- and C-band). During TCs, most high-resolution surface observations are impeded by considerable "rain contamination." Under these conditions, high-resolution surface observations typically come from operational aircraft. Other techniques that provide high-resolution surface observations through rain are also hindered somewhat by rain contamination and are very sparse in space and time. The impacts of rain are functions of the remotely sensed wavelength and rain–drop size. Therefore, relative long wavelengths have been used to observe the surface, but at the cost of a larger footprint. We examine how smaller footprint sizes could be used to observe through gaps between moderate to heavy rainbands that circulate around the main low-pressure center of a TC. Aircraft data from the National Oceanic and Atmospheric Administration’s (NOAA’s) WP-3D turboprop aircraft will be used to create realistic maps of rain. Our results provide information on the satellite instrument characteristics needed to see the surface through these gaps. This information is expected to aid in developing hurricane-related applications of new higher-resolution satellites.

The diurnal cycle of tropical cyclones (TCs) is a daily cycle in clouds that appears in satellite images and may have implications for TC structure and intensity. The diurnal pattern can be seen in infrared (IR) satellite imagery as cyclical pulses in the cloud field that propagate radially outward from the center of nearly all Atlantic-basin TCs. These diurnal pulses, a distinguishing characteristic of this diurnal cycle, begin forming in the storm’s inner core near sunset each day, appearing as a region of cooling cloud-top temperatures. The area of cooling takes on a ring-like appearance as cloud-top warming occurs on its inside edge and the cooling moves away from the storm overnight, reaching several hundred kilometers from the circulation center by the following afternoon. The state-of-the-art TC diurnal cycle measurement in IR satellite imagery has a limited ability to analyze the behavior beyond qualitative observations. We present a method for quantifying the TC diurnal cycle using one-dimensional persistent homology, a tool from Topological Data Analysis, by tracking maximum persistence and quantifying the cycle using the discrete Fourier transform. Using Geostationary Operational Environmental Satellite IR imagery from Hurricanes Felix and Ivan, our method is able to detect an approximate daily cycle.

Using a 13-year dataset of Atmospheric Infrared Sounder (AIRS) retrieved temperature profiles including 5019 AIRS overpasses in 1061 tropical storm through category-2 tropical cyclones (TCs) in global basins during 2002–2014, this study examines the relationship between the warm-core structure and TC intensity change with a focus on rapid intensification (RI). The AIRS TC overpasses are classified into RI, slowly intensifying (SI), neutral (N), and weakening (W) categories. The effect of the warm-core structure upon TC intensification is entangled with that upon TC intensity. It is necessary to exclude the weakening category in order to single out the relationship between TC intensification and warm-core structure from a statistical method. The composite warm-core maximum temperature anomaly is the strongest in RI storms (~7 K), followed by W (~6 K), SI (~5 K), and N (~ 4 K) storms. RI storms have the highest equivalent potential temperature (θ_e) and convective available potential energy (CAPE) in the eye among all intensity change categories. The warm-core structure of RI storms is asymmetric relative to shear, with the higher temperature anomaly and CAPE located in the down-shear quadrant. When only considering samples with intensification rates ≥0, a significant and positive correlation is found between the warm-core strength and TC intensification rate. The warm-core height is also positively correlated with the TC intensification rate at a high confidence level. The AIRS-derived warm-core temperature anomaly greater than 4 K and weighted warm-core height higher than 450 hPa are the necessary conditions for RI.

Field operations and data impact studies examine how observations from high-altitude unmanned aircraft can improve forecasts of tropical cyclones and other high-impact weather events. The National Oceanic and Atmospheric Administration’s (NOAA) Sensing Hazards with Operational Unmanned Technology (SHOUT) project evaluated the ability of observations from high-altitude unmanned aircraft to improve forecasts of high-impact weather events like tropical cyclones or mitigate potential degradation of forecasts in the event of a future gap in satellite coverage. During three field campaigns conducted in 2015 and 2016, the National Aeronautics and Space Administration (NASA) Global Hawk, instrumented with GPS dropwindsondes and remote sensors, flew 15 missions sampling 6 tropical cyclones and 3 winter storms. Missions were designed using novel techniques to target sampling regions where high model forecast uncertainty and a high sensitivity to additional observations existed. Data from the flights were examined in real time by operational forecasters, assimilated in operational weather forecast models, and applied post-mission to a broad suite of data impact studies. Results from the analyses spanning different models and assimilation schemes, though limited in number, consistently demonstrate the potential for positive forecast impact from the observations, both with and without a gap in satellite coverage. The analyses with the then-operational modeling system demonstrated large forecast improvements near 15% for tropical cyclone track at a 72-h lead time when the observations were added to the otherwise complete observing system. While future decisions regarding use of the Global Hawk platform will include budgetary considerations, and more observations are required to enhance statistical significance, the scientific results support the potential merit of the observations. This article provides an overview of the missions flown, observational approach, and highlights from the completed and ongoing data impact studies.

The impacts of the Madden–Julian Oscillation (MJO), Kelvin waves, and Equatorial Rossby (ER) waves on the diurnal cycle of rainfall and types of deep convection over the Maritime Continent are investigated using rainfall from the Tropical Rainfall Measurement Mission Multisatellite Precipitation Analysis and Infrared Weather States (IR–WS) data from the International Satellite Cloud Climatology Project. In an absolute sense, the MJO produced its strongest modulations of rainfall and organized deep convection over the islands, when and where convection is already strongest. The MJO actually has a greater percentage modulation over the coasts and seas, but it does not affect weaker diurnal cycle there. Isolated deep convection was also more prevalent over land during the suppressed phase, while organized deep convection dominated the enhanced phase, consistent with past work. This study uniquely examined the effects of Kelvin and ER waves on rainfall, convection, and their diurnal cycles over the Maritime Continent. The modulation of convection by Kelvin waves closely mirrored that by the MJO, although the Kelvin wave convection continued farther into the decreasing phase. The signals for ER waves were also similar but less distinct. An improved understanding of how these waves interact with convection could lead to improved subseasonal forecast skill.

This study examines how the structure and amount of cloud ice water content are related to rates of tropical cyclone (TC) intensification using CloudSat profiling radar measurements and simulations from the Hurricane Weather Research and Forecasting (HWRF) model. Observational studies have demonstrated the signal of TC intensification in the passive satellite measurements of frozen water concentration. However, the vertical and horizontal resolution of passive satellite observations are limited. CloudSat measurements and HWRF simulations provide high‐resolution data sets of ice water content to better understand its relationship with the rate of TC intensification. It is found that rapidly intensifying TCs have larger ice water content compared to TCs with slower intensification rates. Similar results are obtained even after accounting for the effect of initial TC intensity. Such precursors of rapidly intensifying TCs may be used to better understand and improve the prediction of TC intensification.

Previous studies have noted a relationship between African dust and Atlantic tropical cyclone (TC) activity. However, due to the limitations of past dust analyses, the strength of this relationship remains uncertain. The emergence of aerosol reanalyses, including the Navy Aerosol Analysis and Prediction System (NAAPS) aerosol optical depth (AOD) reanalysis, NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and ECMWF Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA), enables an investigation of the relationship between African dust and TC activity over the tropical Atlantic and Caribbean in a consistent temporal and spatial manner for 2003–2018. Although June–July–August (JJA) 550 nm dust AOD (DAOD) from all three reanalysis products correlates significantly over the tropical Atlantic and Caribbean, the difference in DAOD magnitude between products can be as large as 60 % over the Caribbean and 20 % over the tropical North Atlantic. Based on the three individual reanalyses, we have created an aerosol multi-reanalysis consensus (MRC). The MRC presents overall better root mean square error over the tropical Atlantic and Caribbean compared to individual reanalyses when verified with ground-based AErosol RObotic NETwork (AERONET) AOD measurements. Each of the three individual reanalyses and the MRC have significant negative correlations between JJA Caribbean DAOD and seasonal Atlantic accumulated cyclone energy (ACE), while the correlation between JJA tropical North Atlantic DAOD and seasonal ACE is weaker. Possible reasons for this regional difference are provided. A composite analysis of 3 high-JJA-Caribbean-DAOD years versus 3 low-JJA-Caribbean-DAOD years reveals large differences in overall Atlantic TC activity. We also show that JJA Caribbean DAOD is significantly correlated with large-scale fields associated with variability in interannual Atlantic TC activity including zonal wind shear, mid-level moisture, and sea surface temperature (SST), as well as the El Niño–Southern Oscillation (ENSO) and the Atlantic Meridional Mode (AMM), implying confounding effects of these factors on the dust–TC relationship. We find that seasonal Atlantic DAOD and the AMM, the leading mode of coupled Atlantic variability, are inversely related and intertwined in the dust–TC relationship. Overall, DAOD in both the tropical Atlantic and Caribbean is negatively correlated with Atlantic hurricane frequency and intensity, with stronger correlations in the Caribbean than farther east in the tropical North Atlantic.

This study evaluates precipitation properties involved in tropical cyclogenesis by analyzing a multi-year, global database of passive microwave overpasses of the pre-genesis stage of developing disturbances and nondeveloping disturbances. Precipitation statistics are quantified using brightness temperature proxies from the 85–91-GHz channels of multiple spaceborne sensors, as well as retrieved rain rates. Proxies focus on the overall raining area, areal coverage of deep convection, and the proximity of precipitation to the disturbance center. Of interest are the differences in those proxies for developing versus nondeveloping disturbances, how the properties evolve during the pre-genesis stage, and how they differ globally. The results indicate that of all of the proxies examined, the total raining area and rain volume near the circulation center are the most useful precipitation-related predictor for genesis. The areal coverage of deep convection also differentiates developing from nondeveloping disturbances and, similar to the total raining area, generally also increases during the pre-genesis stage, particularly within a day of genesis. As the threshold convective intensity is increased, pre-genesis cases are less distinguishable from nondeveloping. Compared to the western Pacific and Indian Oceans, the Atlantic and eastern North Pacific have less precipitation and deep convection observed during genesis and the smallest differences between developing and nondeveloping disturbances. This suggests that the total raining area and areal coverage of deep convection associated with tropical disturbances are better predictors of tropical cyclogenesis fate in the Pacific and Indian Oceans than in the Atlantic and eastern North Pacific.

We briefly review the use of Observing System Simulation Experiments in the U.S. and discuss their values and limitations, leading to an expert consensus on five recommendations for moving forward. The NOAA Science Advisory Board appointed a Task Force to prepare a white paper on the use of Observing System Simulation Experiments (OSSEs). Considering the importance and timeliness of this topic and based on this white paper, here we briefly review the use of OSSEs in the U.S., discuss their values and limitations, and develop five recommendations for moving forward: national coordination of relevant research efforts; acceleration of OSSE development for Earth system models; consideration of the potential impact on OSSEs of deficiencies in the current data assimilation and prediction system; innovative and new applications of OSSEs; and extension of OSSEs to societal impacts. OSSEs can be complemented by calculations of forecast sensitivity to observations, which simultaneously evaluate the impact of different observation types in a forecast model system.

This paper reviews the evolution of planetary boundary layer (PBL) parameterization schemes that have been used in the operational version of the Hurricane Weather Research and Forecasting (HWRF) model since 2011. Idealized simulations are then used to evaluate the effects of different PBL schemes on hurricane structure and intensity. The original Global Forecast System (GFS) PBL scheme in the 2011 version of HWRF produces the weakest storm, while a modified GFS scheme using a wind-speed dependent parameterization of vertical eddy diffusivity (K_m) produces the strongest storm. The subsequent version of the hybrid eddy diffusivity and mass flux scheme (EDMF) used in HWRF also produces a strong storm, similar to the version using the wind-speed dependent K_m. Both the intensity change rate and maximum intensity of the simulated storms vary with different PBL schemes, mainly due to differences in the parameterization of K_m. The smaller the K_m in the PBL scheme, the faster a storm tends to intensify. Differences in hurricane PBL height, convergence, inflow angle, warm-core structure, distribution of deep convection, and agradient force in these simulations are also examined. Compared to dropsonde and Doppler radar composites, improvements in the kinematic structure are found in simulations using the wind-speed dependent K_m and modified EDMF schemes relative to those with earlier versions of the PBL schemes in HWRF. However, the upper boundary layer in all simulations is much cooler and drier than that in dropsonde observations. This model deficiency needs to be considered and corrected in future model physics upgrades.

Recent studies have suggested that the structure of tropical cyclones (TCs), especially the upper‐level clouds as indicated by satellite infrared brightness temperatures and precipitation, fluctuates with the diurnal cycle. The diurnal cycle of the low‐level structure, including the boundary layer, has not yet been investigated with observations. This study analyzes data from 2242 GPS dropsondes collected in mature hurricanes to investigate the diurnal variation of the mean boundary layer structure. A composite analysis is conducted to compare the kinematic and thermodynamic structure during nighttime (0–6 local time) versus in the afternoon (12–18 local time). The composites show that much stronger inflow occurs during nighttime and the moist entropy is also larger than that in the daytime. Grouping the dropsonde data into 6‐h time windows relative to the local time shows a clear diurnal signal of boundary layer inflow. The amplitude of the diurnal signal is largest at a radius of 250–500 km.

The Hong Kong Observatory conducted six flights in the atmospheric boundary layer of five tropical cyclones: tropical storm Jebi (1309), typhoon Kalmaegi (1415), severe tropical storm Linfa (1510), typhoon Mujigae (1522), and severe typhoon Nida (1604). Three-dimensional wind data with a 20-Hz sampling rate were available for a height range of 500–670 m, with the mean wind speed from these low-level flights ranging from 10 to 62 m s⁻¹. The turbulent momentum flux and turbulence kinetic energy (e) are measured using the eddy-correlation method, while horizontal scales of turbulent eddies, vertical eddy diffusivity (K), and the vertical turbulent mixing length scale are estimated indirectly. The dependence of the momentum flux, e, K, and the vertical mixing length on wind speed and height are compared with previous studies. Both the momentum flux and turbulent kinetic energy increase with the wind speed, although the rate of increase is smaller for higher wind speeds. It is also found that K increases with wind speed according to a power law up to 40 m s⁻¹ before levelling off, while the vertical mixing length is nearly constant at 100 m. The results serve as a reference for evaluating and improving the turbulent parametrizion in tropical-cyclone models, while the observed large turbulent mixing near the top of the inflow layer of the eyewall region should not be neglected in numerical models.

Turbulence over the mobile ocean surface has distinct properties compared to turbulence over land. Thus, findings that are based on the turbulent kinetic energy (TKE) budget and Monin–Obukhov similarity theory (MOST) over land may not be applicable to conditions over ocean partly because of the existence of a wave boundary layer (the lower part of atmospheric boundary layer including effects of surface waves; we used the term "WBL" in this article for convenience), where the total stress can be separated into turbulent stress and wave coherent stress. Here the turbulent stress is defined as the stress generated by wind shear and buoyancy, while the wave coherent stress accounts for the momentum transfer between ocean waves and atmosphere. In this study, applicability of the turbulent kinetic energy (TKE) budget and the inertial dissipation method (IDM) in the context of the MOST within the WBL are examined. It was found that turbulent transport terms in the TKE budget should not be neglected when calculating the total stress under swell conditions. This was confirmed by observations made on a fixed platform. The results also suggested that turbulent stress, rather than total stress, should be used when applying the MOST within the WBL. By combining the TKE budget and MOST, our study showed that the stress computed by the traditional IDM corresponds to the turbulent stress rather than the total stress. The swell wave coherent stress should be considered when applying the IDM to calculate the stress in the WBL.

The axisymmetric structure of the inner-core hurricane boundary layer (BL) during intensification [IN; intensity tendency ≥ 20 kt (24 h)⁻¹], weakening [WE; intensity tendency < −10 kt (24 h)⁻¹], and steady-state [SS; the remainder] periods are analyzed using composites of GPS dropwindsondes from reconnaissance missions between 1998 and 2015. A total of 3,091 dropsondes were composited for analysis below 2.5 km elevation—1,086 during IN, 1,042 during WE, and 963 during SS. In non-intensifying hurricanes, the lowlevel tangential wind is greater outside the radius of maximum wind (RMW) than for intensifying hurricanes, implying higher inertial stability (I) at those radii for non-intensifying hurricanes. Differences in tangential wind structure (and I) between the groups also imply differences in secondary circulation. The IN radial inflow layer is of nearly equal or greater thickness than nonintensifying groups, and all groups show an inflow maximum just outside the RMW. Non-intensifying hurricanes have stronger inflow outside the eyewall region, likely associated with frictionally forced ascent out of the BL and enhanced subsidence into the BL at radii outside the RMW. Equivalent potential temperatures (θ_e) and conditional stability are highest inside the RMW of non-intensifying storms, which is potentially related to TC intensity. At greater radii, inflow layer θ_e is lowest in WE hurricanes, suggesting greater subsidence or more convective downdrafts at those radii compared to IN and SS hurricanes. Comparisons of prior observational and theoretical studies are highlighted, especially those relating BL structure to large-scale vortex structure, convection, and intensity.

Hurricane Joaquin (2015) was characterized by high track forecast uncertainty when it approached the Bahamas from 29 September 2015 to 01 October 2015, with five-day track predictions ranging from landfall on the United States to east of Bermuda. The source of large track spread in Joaquin forecasts is investigated using an ensemble prediction system (EPS) based on the Hurricane Weather Research and Forecasting (HWRF) model. For the first time, a high-resolution analysis of an HWRF-based EPS is performed to isolate the factors that control tropical cyclone (TC) track uncertainty. Differences in the synoptic-scale environment, the TC vortex structure, and the TC location are evaluated to understand the source of track forecast uncertainty associated with Joaquin, especially at later lead times when U.S. landfall was possible. EPS members that correctly propagated Joaquin into the central North Atlantic are compared with members that incorrectly predicted U.S. landfall. Joaquin track forecasts were highly dependent on the evolution of the environment, including weak atmospheric steering flow near the Bahamas and three synoptic-scale systems: a trough over North America, a ridge to the northeast of Joaquin, and an upper-tropospheric trough to the east of Joaquin. Differences in the steering flow were associated with perturbations of the synoptic-scale environment at the model initialization time. Ultimately, members that produced a more progressive mid-latitude synoptic-scale pattern had reduced track errors. Joaquin track forecast uncertainty was not sensitive to the TC vortex structure or the initial TC position.

This paper describes an analysis and prioritization process for a future NOAA observational system from space, with emphasis on operational applications. Over a 2-year period beginning in 2015, a panel of subject matter experts, the Space Platform Requirements Working Group (SPRWG), carried out an analysis and prioritization of different space-based observations supporting NOAA’s operational services in the areas of weather, oceans, and space weather. NOAA leadership used the SPRWG analysis of space-based observational priorities in different mission areas, among other inputs, to inform the Multi-Attribute Utility Theory (MAUT) based value model and the NOAA Satellite Observing Systems Architecture (NSOSA) study (Volz et al., 2016; NOAA, 2018). The goal of the NSOSA study is to develop candidate satellite architectures for the era beginning in approximately 2030. The SPRWG analysis included a prioritized list of observational objectives together with the quantitative attributes of each objective at three levels of performance, a threshold level of minimal utility, an intermediate level that the community expects by 2030, and a maximum effective level, a level for which further improvements would not be cost effective. This process is believed to be unprecedented in the analysis of long-range plans for providing observations from space. This paper describes the process for developing the prioritized objectives and their attributes and how they were combined in the EDR (Environmental Data Record) Value Model (EVM). The EVM helped inform NOAA’s assessment of many potential architectures for its future observing system within the NSOSA study. However, neither the SPRWG nor its report represents official NOAA policy positions or decisions and the responsibility for selecting and implementing the final architecture rests solely with NOAA senior leadership.

The Global Positioning System (GPS) Radio Occultation (RO) technique allows valuable information to be obtained about the state of the atmosphere through vertical profiles obtained at various processing levels. From the point of view of data assimilation, there is a consensus that less processed data are preferable because of their lowest addition of uncertainties in the process. In the GPSRO context, bending angle data are better to assimilate than refractivity or atmospheric profiles; however, these data have not been properly explored by data assimilation at the CPTEC (acronym in Portuguese for Center for Weather Forecast and Climate Studies). In this study, the benefits and possible deficiencies of the CPTEC modeling system for this data source are investigated. Three numerical experiments were conducted, assimilating bending angles and refractivity profiles in the Gridpoint Statistical Interpolation (GSI) system coupled with the Brazilian Global Atmospheric Model (BAM). The results highlighted the need for further studies to explore the representation of meteorological systems at the higher levels of the BAM model. Nevertheless, more benefits were achieved using bending angle data compared with the results obtained assimilating refractivity profiles. The highest gain was in the data usage exploring 73.4% of the potential of the RO technique when bending angles are assimilated. Additionally, gains of 3.5% and 2.5% were found in the root mean square error values in the zonal and meridional wind components and geopotencial height at 250 hPa, respectively.

At any given time, a tropical cyclone (TC) vortex has multiple intensity pathways that are possible. We conceptualize this problem as a scenario where each of the TC's intensity pathways is a distinct attractor basin, and a combination of several external and internal factors across multiple scales dictates as to which of the many pathways the TC vortex actually takes. As with any complex system, it is difficult to know the details of the multiscale processes that cause or initiate the tipping of the TC vortex into an attractor basin. A stochastic shock arising from any of the various scales within a TC vortex and the subsequent cross‐scale energy transactions may rapidly increase the probability of the vortex intensifying or weakening. To address this problem and apply our conceptual framework to actual TC case studies, we formulate a novel scale‐specific stochastic model that examines the multiscale energetics at and across individual wave numbers within the TC vortex. The stochastic term is modeled in a realistic manner in that the lower and higher wave numbers are treated differently. High‐resolution Hurricane Weather and Research Forecast model outputs of two Bay of Bengal TCs, Phailin (intensifying) and Lehar (weakening), are used as case studies. An ensemble of intensity pathways is generated, and the nonstationary probability distributions of the intensity transitions at each time are examined. Our approach is another step toward an improved understanding of the stochastic dynamics of multiscale transitions of a TC vortex.

We present a numerical investigation of the processes that influenced the contrasting rapid intensity changes in Tropical Cyclones (TC) Phailin and Lehar (2013) over the Bay of Bengal. Our emphasis is on the significant differences in the environments experienced by the TCs within a few weeks and the consequent differences in their organization of vortex-scale convection that resulted in their different rapid intensity changes. The storm-relative proximity, intensity, and depth of the subtropical ridge resulted in the establishment of a low-sheared environment for Phailin and a high-sheared environment for Lehar. Our primary finding here is that in Lehar’s sheared vortex, the juxtaposition in the azimuthal phasing of the asymmetrically distributed downward eddy flux of moist-entropy through the top of the boundary layer, and the radial eddy flux of moist-entropy within the boundary layer in the upshear left-quadrant of Lehar (40–80 km radius) establishes a pathway for the low moist-entropy air to intrude into the vortex from the environment. Conversely, when the azimuthal variations in boundary layer moist-entropy, inflow, and convection are weak in Phailin’s low-sheared environment, the inflow magnitude and radial location of boundary layer convergence relative to the radius of maximum wind dictated the rapid intensification.

Predicting rapid intensity changes in tropical cyclones (TCs) is a major challenge due to the influence of multiple competing processes within the vortex and in the TC environment. We present an empirical framework that quantifies the relative importance of the various factors that influence critical transitions in TC intensities. Our analysis of model simulations of recent TCs over the Bay of Bengal identifies the following variables within the vortex as the biggest influence on TC rapid intensity changes: the amplitudes of wave number 1 of 700‐ to 850‐mb horizontal moisture flux convergence and precipitation in the rainband region and the amplitude of wave number 0 of precipitation within the radius of maximum winds. Likewise, the most important environmental variables identified are the angle between the driest air and the shear vector and the magnitude of vertical wind shear. These findings provide guidance on guidance for future observational efforts and data assimilation into TC forecasting models.

Strengths and weakness of remotely sensed winds are discussed, along with the current capabilities for remotely sensing winds and stress. Future missions are briefly mentioned. The observational needs for a wide range of wind and stress applications are provided. These needs strongly support a short list of desired capabilities of future missions and constellations.

Understanding physical processes leading to rapid intensification (RI) of tropical cyclones (TCs) under environmental vertical wind shear (VWS) is key to improving TC intensity forecasts. This study analyzes the thermodynamic processes that help saturate the TC inner core before RI onset using a column‐integrated moist static energy (MSE) framework. Results indicate that the nearly‐saturated inner core in the lower‐middle troposphere is achieved by an increase in the column‐integrated MSE, as column water vapor accumulates while the mean column temperature cools. The sign of the column‐integrated MSE tendency depends on the competition between surface enthalpy fluxes, radiation, and VWS‐induced ventilation effect. The reduction of ventilation above the boundary layer due to vertical alignment is crucial to accumulate the energy within the inner‐core region. A comparison of the RI simulation with a null simulation further highlights the impact of vortex structure on the thermodynamic state adjustment and TC intensification.

The NASA Cyclone Global Navigation Satellite System (CYGNSS) was launched in December 2016, providing an unprecedented opportunity to obtain ocean surface wind speeds including wind estimates over the hurricane inner‐core region. This study demonstrates the influence of assimilating an early version of CYGNSS observations of ocean surface wind speeds on numerical simulations of two notable landfalling hurricanes, Harvey and Irma (2017). A research version of the National Centers for Environmental Prediction operational Hurricane Weather Research and Forecasting model and the Gridpoint Statistical Interpolation‐based hybrid ensemble three‐dimensional variational data assimilation system are used. It is found that the assimilation of CYGNSS data results in improved track, intensity, and structure forecasts for both hurricane cases, especially for the weak phase of a hurricane, implying potential benefits of using such data for future research and operational applications.

Over the past decade, measurements from the climate-oriented ocean observing system have been key to advancing the understanding of extreme weather events that originate and intensify over the ocean, such as tropical cyclones (TCs) and extratropical bomb cyclones (ECs). In order to foster further advancements to predict and better understand these extreme weather events, a need for a dedicated observing system component specifically to support studies and forecasts of TCs and ECs has been identified, but such a system has not yet been implemented. New technologies, pilot networks, targeted deployments of instruments, and state-of-the art coupled numerical models have enabled advances in research and forecast capabilities and illustrate a potential framework for future development. Here, applications and key results made possible by the different ocean observing efforts in support of studies and forecasts of TCs and ECs, as well as recent advances in observing technologies and strategies are reviewed. Then a vision and specific recommendations for the next decade are discussed.

The diurnal cycle of tropical convection and tropical cyclones (TCs) has been previously described in observational, satellite, and modeling based studies. The main objective of this work is to expand on these earlier studies by identifying signals of the TC diurnal cycle (TCDC) in a hurricane nature run, characterize their evolution in time and space, and better understand the processes that cause them. Based on previous studies that identified optimal conditions for the TCDC, a select period of the hurricane nature run is examined when the simulated storm was intense, in a low shear environment, and sufficiently far from land. When analyses are constrained by these conditions, marked radially propagating diurnal signals in radiation, thermodynamics, winds, and precipitation that affect a deep layer of the troposphere become evident in the model. These propagating diurnal signals, or TC diurnal pulses, are a distinguishing characteristic of the TCDC and manifest as a surge in upper-level outflow with underlying radially propagating tropical squall line-like features. The results of this work support previous studies that examined the TCDC using satellite data and have implications for numerical modeling of TCs and furthering our understanding of how the TCDC forms, evolves, and possibly impacts TC structure and intensity.

The state-of-the-art in intensity forecasting is provided using the Hurricane Weather Research and Forecasting (HWRF) modeling system as the basis. A brief review of existing axisymmetric theory for the intensification of tropical cyclones (TCs) is also provided. Two cloud-resolving simulations from HWRF, one from an idealized case and another from a retrospective forecast of Super Cyclone Phalin (2013), are used to understand the axisymmetric, rapid intensification (RI) process. However, TCs are rarely axisymmetric. The asymmetric structure in the inner core of a TC may be generated by both internal dynamics and external forcing due to environmental factors such as shear and moisture. We use a retrospective HWRF run from Atlantic Hurricane Earl (2010) to understand the role of shear-induced asymmetries on the RI of TCs. We seek to address the following questions: How do TCs rapidly intensify in a sheared environment? What is the role of eddy fluxes on TC intensification? Is the well-accepted theoretical framework of TC intensification still valid for sheared storms undergoing RI? Our findings show that eddy radial vorticity fluxes play a significant role in controlling TC intensity changes in sheared storms. In the case of Earl, despite persistent environmental shear and a lack of symmetric convection, a positive eddy vorticity flux in the middle to upper troposphere created by mesoscale convective complexes had a profound influence in accelerating the TC spin-up process. RI does not occur until persistent convective bursts and the collocated vertical vorticity are concentrated in the downshear-left quadrant about 50 km from the surface center, followed by the propagation of these complexes in an upshear direction. When convective bursts reach the upshear-left quadrant, a nearly symmetric pattern of eddy radial vorticity flux surrounds the center, indicating vorticity anomalies have merged to create a stronger mean vortex wherein the upper and lower level circulations are better aligned. This process is different from that of an idealized vortex. An idealized vortex intensifies in a shear-free environment where individual vortical hot plumes converge and stretch ambient low-level vorticity into a small-scale anomaly and multiple mergers of these plumes lead to a single stronger vortex in a vorticity rich environment. In the idealized case, the major spin-up of the vortex occurs in the TC boundary layer and eyewall region, while spin-up in the case of Earl appears to be top-down during the early stages of RI. Nevertheless, evidence of stronger spin-up is observed in the boundary layer after Earl’s initial RI phase. Although a fully three-dimensional model is required to understand the real TC intensification problem, when viewed from an axially-averaged framework, the basic axisymmetric theory of intensification is still valid for all cases.

Synthetic aperture radar (SAR) has emerged as a new tool for tropical cyclone (TC) monitoring by providing information on the location of TC centers. However, SAR does not usually cover the entire TC domain due to its limited swath width. In this paper, we develop a procedure to identify the location of the center of a TC when an SAR image only covers the rain band portion of the TC but not the eye. The algorithm is based on both an image processing procedure and the available knowledge of the inherent rain-band structure of a TC. The three-step algorithm includes: 1) applying a Canny edge detector to find the curves associated with rain bands; 2) defining two filter criteria to select the spiral curves that resemble the estimation based on a TC rain-band model; 3) searching for the optimal matching solution using the particle swarm optimization algorithm. Numerical experiments with images without TC eye information show that the proposed method can effectively locate the centers of TCs. We compare the experimental results with the best track data to indicate the accuracy. Then, we compare the inflow angle model and the logarithmic spiral model and find that the inflow angle model is more accurate for TC center identification.

Surface wind speeds in tropical cyclones are important for defining current intensity and intensification. Traditionally, airborne observations provide the best information about the surface wind speeds with the Stepped Frequency Microwave Radiometer (SFMR) providing a key role in obtaining such data. However, the flight patterns conducted by hurricane hunter aircraft are limited in their azimuthal coverage of the surface wind field, resulting in an undersampling of the wind field and consequent underestimation of the peak 10-m wind speed. A previous study provided quantitative estimates of the average underestimate for a very strong hurricane. However, no broader guidance on applying a correction based on undersampling has been presented in detail. To accomplish this task, a modified observing system simulation experiment with five hurricane simulations is used to perform a statistical evaluation of the peak wind speed underestimate over different stages of the tropical cyclone lifecycle. Analysis of numerous simulated flights highlights prominent relationships between wind speed undersampling and storm size, where size is defined by the radius of maximum wind speed (RMW). For example, an intense hurricane with small RMW needs negligible correction while a large-RMW tropical storm requires a 16-19% change. A look-up table of undersampling correction factors as a function of peak SFMR wind speed and RMW is provided to assist the tropical cyclone operations community. Implications for hurricane best track intensity estimates are also discussed using real data from past Atlantic hurricane seasons.

The advanced infrared (IR) and microwave (MW) sounding systems have been providing atmospheric sounding information critical for nowcasting and improving weather forecasts through data assimilation in numerical weather prediction. In recent years, advanced IR and MW sounder systems are being proposed to be onboard CubeSats that are much more cost efficient than traditional satellite systems. An impact study using a regional Observing System Simulation Experiment on a local severe storm (LSS) was carried out to evaluate the alternative of using advanced MW and IR sounders for high-impact weather forecasting in mitigating the potential data gap of the Advanced Technology Microwave Sounder (ATMS) and the Cross-track Infrared Sounder (CrIS) on the Suomi-NPP (SNPP) or Joint Polar Satellite System (JPSS). It was found that either MicroMAS-2 or the CubeSat Infrared Atmospheric Sounder (CIRAS) on a single CubeSat was able to provide a positive impact on the LSS forecast, and more CubeSats with increased data coverage yielded larger positive impacts. MicroMAS-2 has the potential to mitigate the loss of ATMS, and CIRAS the loss of CrIS, on SNPP or JPSS, especially when multiple CubeSats are launched. There are several approximations and limitations to the present study, but these represent efficiencies appropriate to the principal goal of the study—gauging the relative values of these sensors.

Operational numerical models failed to predict the record-setting rapid intensification and rapid over-water weakening of Hurricane Patricia (2015) in the eastern North Pacific basin, resulting in large intensity forecast errors. In an effort to better understand the mesoscale processes contributing to Patricia’s rapid intensity changes, we analyze high-resolution aircraft observations collected on 22–23 October. Spline-based variational analyses are created from observations collected via in situ measurements, Doppler radar, and full-tropospheric dropsonde profiles as part of the Office of Naval Research Tropical Cyclone Intensity (TCI) experiment and the National Oceanic and Atmospheric Administration Intensity Forecasting Experiment (IFEX). We present the first full-tropospheric calculation of the dry, axisymmetric Ertel’s potential vorticity (PV) in a tropical cyclone without relying on balance assumptions. Detailed analyses reveal the formation of a “hollow tower” PV structure as Patricia rapidly approached its maximum intensity, and a subsequent breakdown of this structure during Patricia’s rapid over-water weakening phase. Transforming the axisymmetric PV analyses from radius-height to potential radius-isentropic coordinates reveals that Patricia’s rapid intensification was closely related to the distribution of diabatic heating and eddy mixing. During Patricia’s rapid over-water weakening phase, eddy mixing processes are hypothesized to be the primary factor rearranging the PV distribution near the eye-eyewall region, diluting the PV previously confined to the hollow tower while approximately conserving the absolute circulation.

One‐second wind data on the West Florida Shelf were used to examine turbulent scales from large eddies to small eddies in the atmospheric surface layer within a frequency band from 0.02 to 0.3 Hz (periods from ~1 min to ~3 s). Data were collected at two at‐sea locations spanning 6.5 months. Three events in three wind ranges were examined in exploring the one‐dimensional turbulent power spectra: >14 m/s, wind range I; those between 10 and 14 m/s, wind range II; and those between 5 and 10 m/s, wind range III. Events consisted of ensembles of abutting 30‐min subsets spanning 5.5 to 23 hr. The mean vector wind time scale of T₀ = 30 min was found to be reasonable for the West Florida Shelf region. The first wind range provided the best results, more or less in line with a Kolmogorov −5/3 power law whose mean vector wind speed over 21 subsets (10.5 hr) was nearly 15 m/s. The one‐dimensional turbulent power spectra provided an estimate of the dissipation rate (ε) from which other turbulent quantities could be computed: u*, τ, and C_d (the frictional velocity, the surface stress, and the drag coefficient, respectively). The salient point here is that these quantities were larger than those from previous observational studies. Where the power law was not operant intrinsic turbulent spatial scales ranged from 1 to 0.1 m and provide evidence of anisotropy for frequencies greater than 0.1 Hz.

The Cross‐Calibrated Multiplatform (CCMP) ocean surface wind data set was originally developed by Atlas and coworkers to blend cross‐calibrated satellite winds, in situ data, and wind analyses from numerical weather prediction. CCMP uses a variational analysis method to smoothly blend these data sources into a gap‐free gridded wind estimate every 6 hr. CCMP version 2.0 is currently produced by Remote Sensing Systems using consistently cross‐calibrated satellite winds, in situ data from moored buoys, and background winds from the ERA‐Interim reanalysis. The reanalysis fields are only available after a delay of several months, making it impossible to produce CCMP 2.0 in near real time. Measurements from in situ sources such as moored buoys are also often delayed. To overcome these obstacles and produce a near‐real‐time (NRT) version of CCMP (CCMP‐NRT), two changes are made to the input data sets: The background winds are now the operational 0.25‐degree NCEP analysis winds, and no in situ data are used. This allows CCMP‐NRT to be routinely processed with a latency of less than 48 hr. An intercomparison of the CCMP‐NRT results with CCMP 2.0, and independent measurements from moored buoys shows that CCMP‐NRT provides a modest improvement over the background wind from NCEP in regions where satellite data are available. Analysis shows that the inclusion of in situ measurement in CCMP improves the agreement with these measurements, artificially reducing estimates of the error.

Hurricane Frances (2004) represented an unusual event that produced three consecutive overlapping eyewall replacement cycles (ERCs). Their evolution followed some aspects of the typical ERC. The strong primary eyewalls contracted and outward sloping secondary eyewalls formed near three times the radius of maximum winds. Over time these secondary eyewalls shifted inward, became more upright, and replaced the primary eyewalls. In other aspects, however, the ERCs in Hurricane Frances differed from previously described composites. The outer eyewall wind maxima became stronger than the inner in only 12 hours, versus 25 hours for average ERCs. More than 15 m s^-1 outflow peaked in the upper troposphere during each ERC. Relative vorticity maxima peaked at the surface but extended to middle and upper levels. Mean 200 hPa zonal velocity was often from the east, whereas ERC environments typically have zonal flow from the west. These easterlies were produced by an intense upper anticyclone slightly displaced from the center and present throughout the period of multiple ERCs. Inertial stability was low at almost all azimuths at 175 hPa near the 500 km radius during the period of interest. It is hypothesized that the reduced resistance to outflow associated with low inertial stability aloft induced deep upward motion and rapid intensification of the secondary eyewalls. The annular hurricane index of Knaff et al. (2008) showed that Hurricane Frances met all the criteria for annular hurricanes, which make up only 4% of all storms. It is argued that the annular hurricane directly resulted from the repeated ERCs following Wang’s (2008) reasoning.

The thermodynamic impacts of downdraft-induced cooling/drying and downstream recovery via surface enthalpy fluxes within tropical cyclones (TC) were investigated using dropsonde observations collected from 1996–2017. This study focused on relatively weak TCs (tropical depression, tropical storm, category 1 hurricane) that were subjected to moderate (4.5–11.0 m s⁻¹) levels of environmental vertical wind shear. The dropsonde data were analyzed in a shear-relative framework and binned according to TC intensity change in the 24 hours following the dropsonde observation time, allowing for comparison between storms that underwent different intensity changes. Moisture and temperature asymmetries in the lower troposphere yielded a relative maximum in lower-tropospheric conditional instability in the downshear quadrants and a relative minimum in instability in the upshear quadrants, regardless of intensity change. However, the instability increased as the intensification rate increased, particularly in the downshear quadrants. This was due to increased boundary layer moist entropy relative to the temperature profile above the boundary layer. Additionally, significantly larger surface enthalpy fluxes were observed as the intensification rate increased, particularly in the upshear quadrants. These results suggest that in intensifying storms, enhanced surface enthalpy fluxes in the upshear quadrants allow downdraft-modified boundary layer air to recover moisture and heat more effectively as it is advected cyclonically around the storm. By the time the air reaches the downshear quadrants, the lower-tropospheric conditional instability is enhanced, which is speculated to be more favorable for updraft growth and deep convection.

Coral reefs are exceptionally biodiverse and human dependence on their ecosystem services is high. Reefs experience significant direct and indirect anthropogenic pressures, and provide a sensitive indicator of coastal ocean health, climate change, and ocean acidification, with associated implications for society. Monitoring coral reef status and trends is essential to better inform science, management and policy, but the projected collapse of reef systems within a few decades makes the provision of accurate and actionable monitoring data urgent. The Global Coral Reef Monitoring Network has been the foundation for global reporting on coral reefs for two decades, and is entering into a new phase with improved operational and data standards incorporating the Essential Ocean Variables (EOVs) (www.goosocean.org/eov) and Framework for Ocean Observing developed by the Global Ocean Observing System. Three EOVs provide a robust description of reef health: hard coral cover and composition, macro-algal canopy cover, and fish diversity and abundance. A data quality model based on comprehensive metadata has been designed to facilitate maximum global coverage of coral reef data, and tangible steps to track capacity building. Improved monitoring of events such as mass bleaching and disease outbreaks, citizen science, and socio-economic monitoring have the potential to greatly improve the relevance of monitoring to managers and stakeholders, and to address the complex and multi- dimensional interactions between reefs and people. A new generation of autonomous vehicles (underwater, surface, and aerial) and satellites are set to revolutionize and vastly expand our understanding of coral reefs. Promising approaches include Structure from Motion image processing, and acoustic techniques. Across all systems, curation of data in linked and open online databases, with an open data culture to maximize benefits from data integration, and empowering users to take action, are priorities. Action in the next decade will be essential to mitigate the impacts on coral reefs from warming temperatures, through local management and informing national and international obligations, particularly in the context of the Sustainable Development Goals, climate action, and the role of coral reefs as a global indicator. Mobilizing data to help drive the needed behavior change is a top priority for coral reef observing systems.

A series of papers published recently by the first author introduce a nonlinear filter that operates effectively as a data assimilation method for large-scale geophysical applications. The method uses sequential Monte Carlo techniques adopted by particle filters, which make no parametric assumptions for the underlying prior and posterior error distributions. The filter also treats the underlying dynamical system as a set of loosely coupled systems to effectively localize the effect observations have on posterior state estimates. This property greatly reduces the number of particles – or ensemble members – required for its implementation. For these reasons, the method is called the local particle filter. The current manuscript summarizes algorithmic advances made to the local particle filter following recent tests performed over a hierarchy of dynamical systems. The revised filter uses modified vector weight calculations and probability mapping techniques from earlier studies, and new strategies for improving filter stability in situations where state variables are observed infrequently with very accurate measurements. Numerical experiments performed on low-dimensional data assimilation problems provide evidence that supports the theoretical benefits of the new improvements. As a proof of concept, the revised particle filter is also tested on a high-dimensional application from a real-time weather forecasting system at the NOAA National Severe Storms Laboratory (NSSL). The proposed changes have large implications for researchers applying the local particle filter for real applications, such as data assimilation in numerical weather prediction models.

This study investigates the asymmetric distribution of hurricane boundary layer height scales in a storm-motion-relative framework using global positioning system (GPS) dropsonde observations. Data from a total of 1916 dropsondes collected within four times the radius of maximum wind speed of 37 named hurricanes over the Atlantic basin from 1998 to 2015 are analyzed in the composite framework. Motion-relative quadrant mean composite analyses show that both the kinematic and thermodynamic boundary layer height scales tend to increase with increasing radius in all four motion-relative quadrants. It is also found that the thermodynamic mixed layer depth and height of maximum tangential wind speed are within the inflow layer in all motion-relative quadrants. The inflow layer depth and height of the maximum tangential wind are both found to be deeper in the two front quadrants, and they are largest in the right-front quadrant. The difference in the thermodynamic mixed layer depth between the front and back quadrants is smaller than that in the kinematic boundary layer height. The thermodynamic mixed layer is shallowest in the right-rear quadrant, which may be due to the cold wake phenomena. The boundary layer height derived using the critical Richardson number ( Ric" role="presentation" id="MathJax-Element-1-Frame">Ric ) method shows a similar front-back asymmetry as the kinematic boundary layer height.

This article describes advances in airborne, spaceborne, and ground-based systems and technologies used to observe tropical cyclones (TCs), as well as the applications and products that are derived from them. These descriptions include new instrumentation onboard manned aircraft and the development and use of unmanned aircraft, new spaceborne platforms with extremely high spatial and temporal resolution and the plethora of products that exploit these capabilities, and advances in the observations of TC structure changes that accompany landfall through the use of ground-based remote sensing and in situ technologies. An exciting recent development is the increasing use of these technologies in TC-prone regions throughout the world. This global network of observations helps to improve the understanding and prediction of TCs by providing an improved specification of the atmospheric state as well as a robust evaluation of numerical models; improving situational awareness of the location, intensity, and structure of TCs; and developing and testing theories on TC structure and evolution.

Coral reefs are in decline worldwide. In response to this habitat loss, there are efforts to grow, outplant, and restore corals in many regions. The physical oceanographic habitat of corals—such as sea temperature, waves, ocean currents, and available light—is spatially heterogeneous. We therefore hypothesize that outplant location may affect microbiomes, and ultimately, coral health and restoration success. We evaluated the influence of the physical oceanographic habitat on microbes in wild Porites astreoides and Siderastrea siderea. Tissue samples were collected at four Florida reefs in March, June, and September of 2015. We estimated oceanographic conditions from moored instruments, diver observations, remote sensing data, and numerical models. We analyzed microbiomes using amplicon 16S rRNA high-throughput sequencing data. We found microbial alpha-diversity negatively correlated with in situ sea temperature (which represented both the annual cycle and upwelling), as well as modeled alongshore currents, in situ sea-level, and modeled tide. Microbial beta-diversity correlated positively with significant wave height and alongshore currents from models, remotely-sensed relative turbidity, and in situ temperature. We found that archaea from the order Marine Group II decrease with increases in significant wave height, suggesting that this taxon may be influenced by waves. Also, during times of high wave activity, the relative abundance of bacteria from the order Flavobacteriales increases, which may be due to resuspension and cross-shelf transport of sediments. We also found that bacteria from the order SAR86 increase in relative abundance with increased temperature, which suggests that this taxon may play a role in the coral microbiome during periods of higher temperature. Overall, we find that physical oceanographic variability correlates with the structure of these coral microbiomes in ways that could be significant to coral health.

Aircraft reconnaissance missions remain the primary means of collecting direct measurements of marine atmospheric conditions affecting tropical cyclone formation and evolution. The National Hurricane Center tasks the NOAA G-IV aircraft to sample environmental conditions that may impact the development of a tropical cyclone threatening to make landfall in the United States or its territories. These aircraft data are assimilated into deterministic models and used to produce real-time analyses and forecasts for a given tropical cyclone. Existing targeting techniques aim to optimize the use of reconnaissance observations and partially rely on regions of highest uncertainty in the Global Ensemble Forecast System. Evaluating the potential impact of various trade-offs in the targeting process is valuable for determining the ideal aircraft flight track for a prospective mission. AOML’s Hurricane Research Division has developed a system for performing regional Observing System Simulation Experiments (OSSEs) to assess the potential impact of proposed observing systems on hurricane track and intensity forecasting. This study focuses on improving existing targeting methods by investigating the impact of proposed aircraft observing system designs through various sensitivity studies. G-IV dropsonde retrievals were simulated from a regional Nature Run, covering the life cycle of a rapidly intensifying Atlantic hurricane. Results from sensitivity studies provide insight into improvements for real-time operational synoptic surveillance targeting for hurricanes and tropical storms, where dropsondes released closer to the vortex-environment interface provide the largest impact on the track forecast. All dropsonde configurations provide a positive 2-day impact on intensity forecasts by improving the environmental conditions known to impact tropical cyclone intensity.

This 3-year project was designed to assist in providing data for use in the development of nutrient numeric criteria, as required by the Florida Department of Environmental Protection. Researchers with AOML's Ocean Chemistry and Ecosystems Division conducted field work during the first 2 years of the project, followed by the development of various deliverables, including this final report, which describes in detail four separate efforts: (1) water quality cruises; (2) ocean current measurements; and (3) coral assessments; and (4) microbiological assessments.

This study analyzes high-resolution ship data collected in the Gulf of Mexico during the LAgrangian Submesoscale ExpeRiment (LASER) from January-February 2016 to produce the first reported measurements of dissipative heating in the explicitly non-hurricane atmospheric surface layer. Although typically computed from theory as a function of wind speed cubed, the dissipative heating directly estimated via the turbulent kinetic energy (TKE) dissipation rate is also presented. The dissipative heating magnitude agreed with a previous study that estimated the dissipative heating in the hurricane boundary layer using in-situ aircraft data. Our observations that the 10-meter neutral drag coefficient parameterized using TKE dissipation rate approaches zero slope as wind increases suggests that TKE dissipation and dissipative heating are constrained to a physical limit. Both surface-layer stability and sea state were observed to be important conditions influencing dissipative heating, with the stability determined via TKE budget terms and sea state determined via wave steepness and age using direct shipboard measurements. Momentum and enthalpy fluxes used in the TKE budget are determined using the eddy-correlation method. It is found that the TKE dissipation rate and the dissipative heating are largest in a non-neutral atmospheric surface layer with a sea surface comprised of steep windsea and slow swell waves at a given surface wind speed, whereas the ratio of dissipative heating to enthalpy fluxes is largest in near-neutral stability where the turbulent vertical velocities are near zero.

Tropical cyclone (TC) surface wind asymmetry is investigated by using wind data acquired from an L-band passive microwave radiometer onboard the NASA Soil Moisture Active Passive (SMAP) satellite between 2015 and 2017 over the Northwest Pacific (NWP) Ocean. The azimuthal asymmetry degree is defined as the factor by which the maximum surface wind speed is greater than the mean wind speed at the radius of the maximum wind (RMW). We examined storm motion and environmental wind shear effects on the degree of TC surface wind asymmetry under different intensity conditions. Results show that the surface wind asymmetry degree significantly decreases with increasing TC intensity, but increases with increasing TC translation speed, for tropical storm and super typhoon strength TCs; whereas no such relationship is found for typhoon and severe typhoon strength TCs. However, the degree of surface wind asymmetry increases with increasing wind shear magnitude for all TC intensity categories. The relative strength between the storm translation speed and the wind shear magnitude has the potential to affect the location of the maximum wind speed. Moreover, the maximum degree of wind asymmetry is found when the direction of the TC motion is nearly equal to the direction of the wind shear.

This study investigates the role of the parameterized boundary-layer structure in hurricane intensity change using two retrospective HWRF forecasts of Hurricane Earl (2010) in which the vertical eddy diffusivity (K_m) was modified during physics upgrades. Earl undergoes rapid intensification (RI) in the low-Km forecast as observed in nature, while it weakens briefly before resuming a slow intensification at the RI onset in the high-K_m forecast. Angular momentum budget analysis suggests that K_m modulates the convergence of angular momentum in the boundary layer, which is a key component of the hurricane spin-up dynamics. Reducing K_m in the boundary layer causes enhancement of both the inflow and convergence, which in turn leads to stronger and more symmetric deep convection in the low-K_m forecast than in the high-K_m forecast. The deeper and stronger hurricane vortex with lower static stability in the low-K_m forecast is more resilient to shear than that in the high-K_m forecast. With a smaller vortex tilt in the low- K_m forecast, downdrafts associated with the vortex tilt are reduced, bringing less low-entropy air from the mid-levels to the boundary layer, resulting in a less stable boundary layer. Future physics upgrades in operational hurricane models should consider this chain of multiscale interactions to assess their impact on model RI forecasts.

While turbulence is commonly regarded as a flow feature pertaining to the planetary boundary layer (PBL), intense turbulent mixing generated by cloud processes also exists above the PBL in the eyewall and rainbands of a tropical cyclone (TC). The in-cloud turbulence above the PBL is intimately involved in the development of convective elements in the eyewall and rainbands and consists of a part of asymmetric eddy forcing for the evolution of the primary and secondary circulations of a TC. In this study, we show that the Hurricane Weather Research and Forecasting (HWRF) model, one of the operational models used for TC prediction, is unable to generate appropriate sub-grid-scale (SGS) eddy forcing above the PBL due to a lack of consideration of intense turbulent mixing generated by the eyewall and rainband clouds. Incorporating an in-cloud turbulent-mixing parameterization in the vertical turbulent-mixing scheme notably improves the HWRF model's skills in predicting rapid changes in intensity for several past major hurricanes. While the analyses show that the SGS eddy forcing above the PBL is only about one-fifth of the model-resolved eddy forcing, the simulated TC vortex inner-core structure, secondary overturning circulation, and the model-resolved eddy forcing exhibit a substantial dependence on the parameterized SGS eddy processes. The results highlight the importance of eyewall and rainband SGS eddy forcing to numerical prediction of TC intensification, including rapid intensification at the current resolution of operational models.

The effect of swell waves on atmospheric boundary layer turbulence under low winds was explored using data from a fixed platform located in the South China Sea. The wind spectra, cospectra, and Ogive curve measured at a height of 8 m above the mean sea surface provided direct evidence that wind stress was affected by swell waves. To interpret such phenomena, an improved approach was derived based on the fact that the total wind stress was the vector sum of turbulent stress and wave‐coherent stress. Different from the approaches of earlier studies, our approach did not align the turbulent stress with the mean wind speed. The influence of swell waves on the magnitude and direction of the total wind stress was analyzed using our approach. The results showed that the wave‐coherent stress derived from our data accounted for 32% of the total wind stress. The magnitude and angle of the wind stress changed by swell waves depended on the relative angle between the turbulent stress and swell direction.

In preparation for the launch of the NASA Cyclone Global Navigation Satellite System (CYGNSS), a variety of observing system simulation experiments (OSSEs) were conducted to develop, tune, and assess methods of assimilating these novel observations of ocean surface winds. From a highly detailed and realistic hurricane nature run (NR), CYGNSS winds were simulated with error characteristics that are expected to occur in reality. The OSSE system makes use of NOAA’s HWRF model and GSI data assimilation system in a configuration that was operational in 2012. CYGNSS winds were assimilated as scalar wind speeds and as wind vectors determined by a Variational Analysis Method (VAM). Both forms of wind information had positive impacts on the short-term HWRF forecasts, as shown by key storm and domain metrics. Data assimilation cycle intervals of 1, 3, and 6 hours were tested, and the 3-h impacts were consistently best. One day forecasts from CYGNSS VAM vector winds were the most dynamically consistent with the NR. The OSSEs have a number of limitations, most noteworthy that this is a case study and static background error covariances were used.

Forecasting rapid intensity changes in tropical cyclones (TCs) is hard as the factors responsible span many scales. External and internal dynamical and thermodynamical variables act simultaneously in a nonlinear fashion, either complementing, amplifying, inhibiting or not impacting the TC intensity at all. We try to address the following question: What is the relative importance of the external and vortex-scale variables that influence rapid intensity changes within a TC? Further, which of these variables must be prioritized from an observational standpoint? To answer these questions, a systematic analysis was conducted on a large number of representative TCs to make statistically significant conclusions using discriminant analyses of wavenumber (WN) - filtered fields, with a principal component analysis to detect over-fitting and identify the subset of variables (from the environment and the vortex) consistently correlated with rapid intensity change. Our analyses indicate that a small number of variables wield the most influence on TC rapid intensity changes. The most important variables within the vortex are the WN 0 of precipitation within the radius of maximum winds, the amplitudes of WN 1 of precipitation and the mid-level horizontal moisture flux convergence in the rain band region. Likewise, the most important environmental variables are the angle of the driest air from the shear vector and the magnitude of environmental wind shear. These variables must be prioritized in future observational and consequent data assimilation efforts.

The Time‐Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission was selected by NASA as part of the Earth Venture‐Instrument (EVI‐3) program. The overarching goal for TROPICS is to provide nearly all‐weather observations of 3‐D temperature and humidity, as well as cloud ice and precipitation horizontal structure, at high temporal resolution to conduct high‐value science investigations of tropical cyclones. TROPICS will provide rapid‐refresh microwave measurements (median refresh rate better than 60 minutes for the baseline mission) that can be used to observe the thermodynamics of the troposphere and precipitation structure for storm systems at the mesoscale and synoptic scale over the entire storm lifecycle. TROPICS comprises six CubeSats in three low‐Earth orbital planes. Each CubeSat will host a high performance radiometer to provide temperature profiles using seven channels near the 118.75 GHz oxygen absorption line, water vapor profiles using three channels near the 183 GHz water vapor absorption line, imagery in a single channel near 90 GHz for precipitation measurements (when combined with higher resolution water vapor channels), and a single channel near 205 GHz that is more sensitive to precipitation‐sized ice particles. This observing system offers an unprecedented combination of horizontal and temporal resolution to measure environmental and inner‐core conditions for tropical cyclones on a nearly global scale and is a major leap forward in the temporal resolution of several key parameters needed for assimilation into advanced data assimilation systems capable of utilizing rapid‐update radiance or retrieval data. Launch readiness is currently projected for late 2019.

The simulation of observations—a critical CGOP component—is validated first by comparison of error-free simulated observations for the first 24 h at the start of the nature run (NR) to the real observations for those sensors that operated during that period. Sample results of this validation are presented here for existing low earth orbit (LEO) infrared (IR) and microwave (MW) brightness temperature (BT) observations, for radio occultation (RO) bending angle observations, and for various types of conventional observations. For sensors not operating at the start of the NR, a qualitative validation is obtained by comparing geographic and statistical characteristics of observations over the initial day for such a sensor and an existing similar sensor. Comparisons agree, with no significant unexplained bias, and to within the uncertainties due to real observation errors, time and space collocation differences, radiative transfer uncertainties, and differences between the NR and reality. To validate channels of a proposed future MW sensor with no equivalent existing spaceborne sensor channel, multiple linear regression is used to relate these channels to existing similar channels. The validation then compares observations simulated from the NR to observations predicted by the regression relationship applied to actual real observations of the existing channels. Overall, the CGOP simulations of error-free observations from conventional and satellite platforms that make up the global observing system are found to be reasonably accurate and suitable as a starting point for creating realistic simulated observations for OSSEs. These findings complete a critical step in the CGOP validation, thereby reducing the caveats required when interpreting the OSSE results.

Observing systems simulation experiments (OSSEs) are used to simulate and assess the impacts of new observing systems planned for the future or the impacts of adopting new techniques for exploiting data or for forecasting. This study focuses on impacts of satellite data on global numerical weather prediction (NWP) systems. Since OSSEs are based on simulations of nature and observations, reliable results require that the OSSE system be validated. This validation involves cycles of assessment and calibration of the individual system components, as well as the complete system, with the end goal of reproducing the behavior of real-data observing systems experiments (OSEs). This study investigates the accuracy of the calibration of an OSSE system—here, the Community Global OSSE Package (CGOP) system—before any explicit tuning has been performed by performing an intercomparison of the OSSE summary assessment metrics (SAMs) with those obtained from parallel real-data OSEs. The main conclusion reached in this study is that, based on the SAMs, the CGOP is able to reproduce aspects of the analysis and forecast performance of parallel OSEs despite the simplifications employed in the OSSEs. This conclusion holds even when the SAMs are stratified by various subsets (i.e., the tropics only, temperature only, ...).

On 23 October 2015 at ~1732 UTC, the Airborne Detector for Energetic Lightning Emissions (ADELE) flew through the eyewall of Hurricane Patricia aboard the National Oceanic and Atmospheric Administration’s Hurricane Hunter WP‐3D Orion, aircraft, observing the first terrestrial gamma‐ray flash (TGF) ever seen in that context and the first ever viewed from behind the forward direction of the main TGF gamma‐ray burst. ADELE measured 184 counts of ionizing radiation within 150 μs, coincident with the detection of a nearby lightning flash. Lightning characteristics inferred from the associated radio signal and comparison of the gamma‐ray energy spectrum to simulations suggest that this is the first observation of a reverse beam of positrons predicted by the leading TGF production model, relativistic runaway electron avalanches. This paper presents the first experimental evidence of a previously predicted second component of gamma‐ray emission from TGFs. The brightest emission, commonly observed from orbit, is from the relativistic runaway electron avalanche bremsstrahlung; the second, fainter component reported here is from the bremsstrahlung of positrons propagating in the reverse direction. This reverse gamma‐ray beam penetrates to low enough altitudes to allow ground‐based detection of typical upward TGFs from mountain observatories.

A strong African easterly wave (AEW) left the west African coast in early September 2014 and operational global numerical forecasts suggested a potential for rapid tropical cyclogenesis of this disturbance in the eastern Atlantic, despite the presence of a large region of dry air northwest of the disturbance. Analysis and in-situ observations show that after leaving the coast, the closed circulation associated with the AEW trough was not well aligned vertically and therefore low-level or mid-level dry air was advected below or above (respectively) areas of closed circulation. GPS dropwindsonde observations highlight the dry air undercutting the midlevel recirculation region in the southwestern quadrant. This advection of dry air constrains the spatial extent of deep convection within the AEW trough, leading to the vortex decaying. As the column continues to be displaced horizontally, losing vertical alignment, this enables increased horizontal advection of dry air into the system further limiting convective activity. Ensemble forecasts indicate that short-term errors in precipitation rate and vorticity generation can lead to an over intensified and well aligned vortex which then interacts less with the unfavorable environment, allowing for further convection and intensification. The stronger vortex provides more favorable conditions for precipitation through a more vertically coherent closed circulation and thus a positive feedback loop is initiated. The short-term forecasts of precipitation were shown to be sensitive to lower tropospheric moisture anomalies around the AEW trough through ensemble sensitivity analysis from Global Ensemble Forecast System real-time forecasts.

This study presents wind observations from an airborne Doppler Wind Lidar (ADWL) in 2016 tropical cyclones (TC). A description of ADWL measurement collection and quality control methods is introduced for the use in a TC environment. Validation against different instrumentation onboard the National Oceanographic and Atmospheric Administration’s WP-3D aircraft shows good agreement of the retrieved ADWL measured wind speed and direction. Measurements taken from instruments such as the global positioning system dropsonde, flight-level wind probe, tail Doppler radar, and Stepped Frequency Microwave Radiometer are compared to ADWL observations by creating paired datasets. These paired observations represent independent measurements of the same observation space through a variety of mapping techniques that account for differences in measurement procedure. Despite high correlation values, outliers are identified and discussed in detail. The errors between paired observations appear to be caused by differences in the ability to capture various length scales, which directly relate to certain regions in a TC regime. In validating these datasets and providing evidence that shows the mitigation of gaps in 3-dimensional wind representation, the unique wind observations collected via ADWL have significant potential to impact numerical weather prediction of TCs.

In preparation for the Fourth International Workshop on Tropical Cyclone Landfall Processes (IWTCLP-IV), a summary of recent research studies and the forecasting challenges of tropical cyclone (TC) rainfall has been prepared. The extreme rainfall accumulations in Hurricane Harvey (2017) near Houston, Texas and Typhoon Damrey (2017) in southern Vietnam are examples of the TC rainfall forecasting challenges. Some progress is being made in understanding the internal rainfall dynamics via case studies. Environmental effects such as vertical wind shear and terrain-induced rainfall have been studied, as well as the rainfall relationships with TC intensity and structure. Numerical model predictions of TC-related rainfall have been improved via data assimilation, microphysics representation, improved resolution, and ensemble quantitative precipitation forecast techniques. Some attempts have been made to improve the verification techniques as well. A basic forecast challenge for TC-related rainfall is monitoring the existing rainfall distribution via satellite or coastal radars, or from over-land rain gauges. Forecasters also need assistance in understanding how seemingly similar landfall locations relative to the TC experience different rainfall distributions. In addition, forecasters must cope with anomalous TC activity and landfall distributions in response to various environmental effects.

The impacts of Global Hawk (GH) dropwindsondes on tropical cyclone (TC) analyses and forecasts are examined over a composite sample of missions flown during the NASA Hurricane and Severe Storm Sentinel (HS3) and the NOAA Sensing Hazards with Operational Unmanned Technology (SHOUT) field campaigns. An ensemble Kalman filter is employed to assimilate the dropwindsonde observations at the vortex scale. With the assimilation of GH dropwindsondes, TCs generally exhibit less position and intensity errors, a better wind-pressure relationship, and improved representation of integrated kinetic energy in the analyses. The resulting track and intensity forecasts with all the cases generally show a positive impact when GH dropwindsondes are assimilated. The impact of GH dropwindsondes is further explored with cases stratified for intensity change and presence of crewed aircraft data. GH dropwindsondes demonstrate a larger impact for non-steady-state TCs (non-SS; 24-h intensity change larger than 20 kt) than for steady state (SS) TCs. The relative skill from assimilating GH dropwindsondes ranges between 25-35% for either the position or intensity improvement in the final analyses overall, but only up to 10% for SS cases alone. The resulting forecasts for non-SS cases show higher skill for both track and intensity than SS cases. In addition, the GH dropwindsonde impact on TC forecasts varies in the presence of crewed aircraft data. An increased intensity improvement at long lead times is seen when crewed aircraft data are absent. This demonstrates the importance of strategically designing flight patterns to exploit the sampling strengths of the GH and crewed aircraft in order to maximize data impacts on TC prediction.

This study demonstrates that Global Hawk unmanned aircraft system dropwindsondes and Atmospheric Infrared Sounder (AIRS) observations can be complementary in sampling a tropical cyclone (TC). The assimilation of both datasets in a regional ensemble data assimilation system shows that the cumulative impact of both datasets is greater than either one alone due to the presence of mutually independent information content. The experiment that assimilates both datasets has smaller position and intensity errors in the mean analysis than the ones with individual datasets. The improvements in track and intensity forecasts that result from combining both datasets also indicate synergistic benefits. Overall, superior track and intensity forecasts are evident. This study suggests that polar-orbiting satellite spatial coverage should be considered in operational reconnaissance mission planning in order to achieve further improvements in TC analyses and forecasts.

Experiments with a global Observing System Simulation Experiment (OSSE) system based on the recent 7-km resolution NASA nature run known as the G5NR were conducted to determine the potential value of proposed Global Navigation Satellite System (GNSS) radio occultation (RO) constellations in current operational numerical weather prediction systems. The RO observations were simulated with the geographic sampling expected from the original planned Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) system, with 6 equatorial (total of ~6,000 soundings/day) and 6 polar (total of ~6,000 soundings/day) receiver satellites. The experiments also accounted for the expected improved vertical coverage provided by the Jet Propulsion Laboratory RO receivers onboard COSMIC-2. Except that RO observations were simulated and assimilated as refractivities, the 2015-year version of the NCEP’s operational data assimilation system was used to run the OSSEs. The OSSEs quantified the impact of RO observations on global weather analyses and forecasts, and the impact of adding explicit errors to the simulation of perfect RO profiles. The inclusion or exclusion of explicit errors had small statistically insignificant impacts on results. The impact of RO observations was found to increase the length of the useful forecasts. In experiments with explicit errors, these increases were found to be 0.6 hours in the Northern Hemisphere extratropics (a 0.4% improvement), 5.9 hours in the Southern Hemisphere extratropics (a significant 4.0% improvement), and 12.1 hours in the Tropics (a very substantial 28.4% improvement).

Airborne Doppler radar captured the inner core of Hurricane Earl during the early stages of secondary eyewall formation (SEF), providing needed insight into the SEF dynamics. An organized rainband complex outside of the primary eyewall transitioned into an axisymmetric secondary eyewall containing a low-level tangential wind maximum. During this transition, the downshear-left quadrant of the storm exhibited several notable features. A mesoscale descending inflow (MDI) jet persistently occurred across broad stretches of stratiform precipitation in a pattern similar to previous studies. This negatively buoyant jet travelled radially inward and descended into the boundary layer. Radially inward, enhanced low-level inflow and intense updrafts appeared. The updraft adjacent to the MDI was likely triggered by a region of convergence and upward acceleration (induced by the negatively buoyant MDI) entering the high-θ_e boundary layer. This updraft and the MDI in the downshear-left quadrant accelerated the tangential winds in a radial range where the axisymmetric wind maximum of the secondary eyewall soon developed. This same quadrant eventually exhibited the strongest overturning circulation and wind maximum of the forming secondary eyewall. Given these features occurring in succession in the downshear-left quadrant, we hypothesize that the MDI plays a significant dynamical role in SEF. The MDI within a mature rainband complex persistently perturbs the boundary layer, which locally forces enhanced convection and tangential winds. These perturbations provide steady low-level forcing that projects strongly onto the axisymmetric field, and forges the way for secondary eyewall development via one of several SEF theories that invoke axisymmetric dynamical interactions.

Hurricane Bonnie (1998) was an unusually resilient hurricane that maintained a steady-state intensity while experiencing strong (12–16 m s⁻¹) vertical wind shear and an eyewall replacement cycle. This remarkable behavior was examined using observations from flight-level data, microwave imagery, radar, and dropsondes over the two-day period encompassing these events. Similar to other observed eyewall replacement cycles, Bonnie exhibited the development, strengthening, and dominance of a secondary eyewall while a primary eyewall decayed. However, Bonnie’s structure was highly asymmetric due to the large vertical wind shear, in contrast to the more symmetric structures observed in other hurricanes undergoing eyewall replacement cycles. It is hypothesized that the unusual nature of Bonnie’s evolution arose due to an increase in vertical wind shear from 2 to 12 m s⁻¹ even as the storm intensified to a major hurricane in the presence of high ambient sea-surface temperatures. These circumstances allowed for the development of outer rainbands with intense convection downshear, where the formation of the outer eyewall commenced. In addition, the circulation broadened considerably during this time. The secondary eyewall developed within a well-defined beta skirt in the radial velocity profile, consistent with earlier theory. Despite the large ambient vertical wind shear, the outer eyewall steadily extended upshear, supported by 35 % larger surface wind speed upshear than downshear. The larger radius of maximum winds during and after the eyewall replacement cycle might have aided Bonnie’s resiliency directly, but also increased the likelihood that diabatic heating would fall inside the radius of maximum winds.

The structure of coherent turbulence in an eyewall replacement cycle in Hurricane Rita (2005) is presented from novel airborne Doppler radar observations using the Imaging Wind and Rain Airborne Profiler (IWRAP). The IWRAP measurements and three-dimensional (3D) wind vector calculations at a grid spacing of 250 m in the horizontal and 30 m in the vertical reveal the ubiquitous presence of organized turbulent eddies in the lower levels of the storm. The data presented here, and the larger collection of IWRAP measurements, currently are the highest resolution Doppler radar, 3D wind vectors ever obtained in a hurricane over the open ocean. Coincident data from NOAA airborne radars, the stepped frequency microwave radiometer and flight level data help to place the IWRAP observations into context and provide independent validation. The typical characteristics of the turbulent eddies are the following: radial wavelengths of ~01–3 km (mean value is ~2 km), depths from the ocean surface up to flight level (~1.5 km), aspect ratio of ~1.3 and horizontal wind speed perturbations of 10–20 m s^-1. The most intense eddy activity is located on the inner edge of the outer eyewall during the concentric eyewall stage with a shift to the inner eyewall during the merging stage. The evolving structure of the vertical wind shear is connected to this shift and together these characteristics have several similarities to boundary layer roll vortices. However, eddy momentum flux analysis reveals that high momentum air is being transported upwards, in contrast with roll vortices, with large positive values (~150 m² s^-2) found in the turbulent filaments. In the decaying, inner eyewall, elevated tangential momentum is also being transported radially outward to the intensifying, outer eyewall. These results indicate that the eddies may have connections to potential vorticity waves with possible modifications due to boundary layer shear instabilities.

The summary assessment metric (SAM) method is applied to an array of primary assessment metrics (PAMs) for the deterministic forecasts of three leading numerical weather prediction (NWP) centers for the years 2015-2017. The PAMs include anomaly correlation, RMSE, and absolute mean error (i.e., the absolute value of bias) for different forecast times, vertical levels, geographic domains, and variables. SAMs indicate that in terms of forecast skill ECMWF is better than NCEP, which is better than but approximately the same as UKMO. The use of SAMs allows a number of interesting features of the evolution of forecast skill to be observed. All three centers improve over the three year period. NCEP short-term forecast skill substantially increases during the period. Quantitatively, the effect of the 2016 May 11 NCEP upgrade to the 4D-ensemble variational (4DEnVar) system is a 7.37% increase in the probability of improved skill relative to a randomly chosen forecast metric from 2015-2017. This is the largest SAM impact during the study period. However, the observed impacts are within the context of slowly improving forecast skill for operational global NWP as compared to earlier years. Clearly the systems lagging ECMWF can improve, and there is evidence from SAMs in addition to the 4DEnVar example that improvements in forecast and data assimilation systems are still leading to forecast skill improvements.

A one-dimensional (1d) analysis problem is defined and analyzed to explore the interaction of observation thinning or superobservation with observation errors that are correlated or systematic. The general formulation might be applied to a 1d analysis of radiance or radio occultation observations in order to develop a strategy for the use of such data in a full data assimilation system, but is applied here to a simple analysis problem with parameterized error covariances. Findings for the simple problem include the following. For a variational analysis method that includes an estimate of the full observation error covariances, the analysis is more sensitive to variations in the estimated background and observation error standard deviations than in the corresponding correlation length scales. Furthermore, if everything else is fixed, the analysis error increases with decreasing true background error correlation length scale and with increasing true observation error correlation length scale. For a weighted least squares analysis method that assumes the observation errors are uncorrelated, best results are obtained for some degree of thinning and/or tuning of the weights. Without tuning, the best strategy is superobservation with a spacing approximately equal to the observation error correlation length scale.

Wind and wave-breaking directions are investigated as potential sources of an asymmetry identified in off-nadir, remotely sensed measurements of ocean surface brightness temperatures obtained by the Stepped-Frequency Microwave Radiometer (SFMR) in high-wind conditions, including in tropical cyclones. Surface wind speed, which dynamically couples the atmosphere and ocean, can be inferred from SFMR ocean surface brightness temperature measurements using a radiative transfer model and inversion algorithm. The accuracy of the ocean surface brightness temperature to wind speed calibration relies on accurate knowledge of the surface variables that are influencing the ocean surface brightness temperature. Previous studies have identified wind direction signals in horizontally polarized radiometer measurements in low to moderate (0-20 m s^-1) wind conditions over a wide range of incidence angles. This study finds that the azimuthal asymmetry in the off-nadir SFMR brightness temperature measurements is also likely a function of wind direction and extends the results of these previous studies to high-wind conditions. The off-nadir measurements from the SFMR provide critical data for improving the understanding of the relationships between brightness temperature, surface wave-breaking direction, and surface wind vectors at various incidence angles, which are extremely useful for the development of geophysical model functions for instruments like the Hurricane Imaging Radiometer (HIRad).

Marine atmospheric boundary layer (MABL) roll plays an important role in the turbulent exchange of momentum, sensible heat, and moisture throughout MABL of tropical cyclone (TC). Hence, rolls are believed to be closely related to a TC’s development, intensification, and decay processes. Spaceborne synthetic aperture radar (SAR) provides a unique capability to image the sea surface imprints of quasi‐linear streaks induced by the MABL rolls within a TC. In this study, 16 SAR images, including three images acquired during three major hurricanes—Irma, Jose, and Maria in the 2017 Atlantic hurricane season—were used to systematically map the distribution and wavelength of MABL rolls under the wide range of TC intensities. The images were acquired by SAR onboard RADARSAT‐1/2, ENVISAT, and SENTINEL‐1 satellites. Our findings are in agreement with the previous one case study of Hurricane Katrina (2005), showing the roll wavelengths are between 600 and 1,600 m. We also find that there exist roll imprints in the eyewall and rainbands, although the boundary layer heights are shallower there. Besides, the spatial distribution of roll wavelengths is asymmetrical. The roll wavelengths are found to be the shortest around the storm center, increase and then decrease with distance from storm center, reaching the peak values in the range of d* ‑ 2d*, where d* is defined as the physical location to TC centers normalized by the radius of maximum wind. These MABL roll characteristics cannot be derived using conventional aircraft and land‐based Doppler radar observations.

This study examines the growth of tropical cyclone (TC) intensity forecast errors and related intensity predictability for the NOAA operational Hurricane Weather Research and Forecasting (HWRF) model. Using operational intensity forecasts during the 2012 to 2016 seasons, two conditions for a limited range of TC intensity predictability are demonstrated, which include (a) the existence of an intensity error saturation limit, and (b) the dependence of the intensity error growth rate on storm intensity during TC development. By stratifying intensity errors based on different initial intensity bins, it is shown that TC intensity error growth rate is relatively small (∼0.3 kt h⁻¹) at the early stage of TC development, but it quickly increases to ∼1 kt h⁻¹ during TC intensification. Of further importance is that the intensity error saturation varies in the range of 14–18 kt in different ocean basins, thus suggesting the potential dependence of the intensity predictability on large‐scale environment. Additional idealized experiments with the HWRF model confirm the saturation of intensity errors, even under a perfect model scenario. The existence of the intensity error saturation together with the finding of a faster error growth rate for higher intensity suggests that the TC dynamics possesses an inherent limited predictability, which prevents us from reducing the intensity errors in TC dynamical models below a certain threshold.

A preliminary investigation into the impact of dropsonde observations from the Global Hawk (GH) on tropical and extratropical forecasts is performed using the National Centers for Environmental Prediction (NCEP) Global Data Assimilation System (GDAS). Experiments are performed during high-impact weather events which were sampled as part of the Sensing Hazards with Operational Unmanned Technology (SHOUT) field campaigns in 2016: (1) three extratropical systems in February 2016, and (2) Hurricanes Matthew and Nicole in the western Atlantic. For these events, the benefits of GH observations under a satellite data gap scenario are also investigated. It is found that the assimilation of GH dropsondes reduces the track error for both Matthew and Nicole; the improvements are as high as 20% beyond 60 hours. Additionally, the localized dropsondes reduce global forecast track error for four tropical cyclones by up to 9%. Results are mixed under a satellite gap scenario, where only Hurricane Matthew is improved from assimilated dropsondes. The improved storm track is attributed to a better representation of the steering flow and atmospheric mid-level pattern. For all cases, dropsondes reduce the root-mean-squared error in temperature, relative humidity, wind, and sea-level pressure by 3-8% out to 96 hours. Additional benefits from GH dropsondes are obtained in precipitation, with higher skill scores over the southeastern United States versus control forecasts of up to 8%, as well as for low-level parameters important for severe weather prediction. The findings from this study are preliminary and, therefore, more cases are needed for statistical significance.

A positive impact of adding directional information to observations from the CYclone Global Navigation Satellite System (CYNGSS) constellation of microsatellites is observed in simulation using a high-resolution nature run of an Atlantic hurricane for a 4-day period. Directional information is added using a 2-dimensional variational analysis method (VAM) for near-surface vector winds that blends simulated CYGNSS wind speeds with an a priori background vector wind field at 6-hour analysis times. The resulting wind vectors at CYGNSS data locations are more geophysically self-consistent when using high-resolution, 6-hour forecast backgrounds from a Hurricane Weather Research and Forecast (HWRF) Control Observing System Simulation Experiment (OSSE) compared to low-resolution 6-hour forecasts from an associated Global Forecast System (GFS) model Control OSSE. An important contributing factor is the large displacement error in the center of circulation in the GFS background wind fields that produces asymmetric circulations in the associated VAM analyses. Results of a limited OSSE indicate that CYGNSS winds reduce forecast error in hurricane intensity in 0-48 hour forecasts compared to using no CYGNSS data. Assimilation of VAM-CYGNSS vector winds reduces maximum wind speed error by 2-5 kts and reduces minimum central pressure error by 2-5 hPa. The improvement in forecast intensity is notably larger and more consistent than the reduction in track error. Assimilation of VAM-CYGNSS wind vectors constrains analyses of surface wind field structures during OSSE more effectively than wind speeds alone. Due to incomplete sampling and the limitations of the data assimilation system used, CYGNSS scalar winds produce unwanted wind/pressure imbalances and asymmetries more often than the assimilation of VAM-CYGNSS data.

Forecasts from the operational Hurricane Weather Research and Forecasting (HWRF) based ensemble prediction system for Hurricane Edouard (2014) are analyzed to study the differences in both the tropical cyclone inner-core structure and large-scale environment between rapidly intensifying (RI) and non-intensifying (NI) ensemble members. An analysis of the inner-core structure reveals that as deep convection wraps around from the downshear side of the storm to the upshear-left quadrant for RI members, vortex tilt and asymmetry reduce rapidly and RI occurs. For NI members, deep convection stays trapped in the downshear/downshear-right quandrant, and storms do not intensify. The budget calculation of tangential wind tendency reveals that the positive radial eddy vorticity flux for RI members contributes significantly to spinning up the tangential wind in the middle and upper levels and reduces vortex tilt. The negative eddy vorticity flux for NI members spins down the tangential wind in the middle and upper levels and does not help the vortex become vertically aligned. An analysis of the environmental flow shows that the cyclonic component of the storm-relative upper-level environmental flow in the left-of-shear quadrants aids the cyclonic propagation of deep convection and helps establish the configuration that leads to the positive radial vorticity flux for RI members. In contrast, the anticyclonic component of the storm-relative middle-and-upper-level environmental flow in the left-of-shear quadrants inhibits the cyclonic propagation of deep convection and suppresses the positive radial eddy vorticity flux for NI members. Environmental moisture in the downshear-right quadrant is also shown to be important for the formation of deep convection for RI members.

This review prepared for the fourth International Workshop on Tropical Cyclone Landfall Processes (IWTCLP-4) summarizes the most recent (2015-2017) theoretical and practical knowledge in the field of tropical cyclone (TC) track, intensity, and structure rapid changes at or near landfall. Although the focus of IWTCLPIV was on landfall, this summary necessarily embraces the characteristics of storms during their course over the ocean prior to and leading up to landfall. In the past few years, extremely valuable observational datasets have been collected for TC forecasting guidance and research studies using both aircraft reconnaissance and new geostationary or low-earth orbiting satellites at high temporal and spatial resolution. Track deflections for systems near complex topography such as that of Taiwan and La Reunion have been further investigated, and advanced numerical models with high spatial resolution necessary to predict the interaction of the TC circulation with steep island topography have been developed. An analog technique has been designed to meet the need for longer range landfall intensity forecast guidance that will provide more time for emergency preparedness. Probabilistic track and intensity forecasts have also been developed to better communicate on forecast uncertainty. Operational practices of several TC forecast centers are described herein and some challenges regarding forecasts and warnings for TCs making landfall are identified. This review concludes with insights from both researchers and forecasters regarding future directions to improve predictions of TC track, intensity, and structure at landfall.

Accurate atmospheric temperature and moisture information with high temporal/spatial resolution are two of the key parameters needed in regional numerical weather prediction (NWP) models to reliably predict high-impact weather events such as local severe storms (LSSs). High spectral resolution or hyperspectral infrared (HIR) sounders from geostationary orbit (GEO) provide an unprecedented source of near time-continuous, three-dimensional information on the dynamic and thermodynamic atmospheric fields—an important benefit for nowcasting and NWP-based forecasting. In order to demonstrate the value of GEO HIR sounder radiances on LSS forecasts, a quick regional OSSE (Observing System Simulation Experiment) framework has been developed, including high-resolution nature run generation, synthetic observation simulation and validation, and impact study on LSS forecasts. Results show that, on top of the existing LEO (low earth orbit) sounders, a GEO HIR sounder may provide value-added impact [a reduction of 3.56% in normalized root-mean-square difference (RMSD)] on LSS forecasts due to large spatial coverage and high temporal resolution, even though the data are assimilated every 6 h with a thinning of 60 km. Additionally, more frequent assimilations and smaller thinning distances allow more observations to be assimilated and may further increase the positive impact from a GEO HIR sounder. On the other hand, with denser and more frequent observations assimilated, it becomes more difficult to handle the spatial error correlation in observations and gravity waves due to the limitations of current assimilation and forecast systems (such as a static background error covariance). The peak reduction of 4.6% in normalized RMSD is found when observations are assimilated every 3 h with a thinning distance of 30 km. 

This study analyzes high‐frequency wind data collected by research towers in the surface layer of Typhoons Hagupit (2008) and Chanthu (2010) to investigate the characteristics of the momentum flux, turbulent kinetic energy (TKE), drag coefficient, and dissipative heating (DH) during landfalls. It is found that the momentum flux TKE and DH increase with the wind speed up to the maximum observed wind speed (~40 m/s), in agreement with previous studies that presented eddy correlation flux data in a similar condition but with lower maximum observed wind speed. However, the momentum flux, TKE, drag coefficient, and DH are found to be substantially larger in Typhoon Chanthu (2010) than those in Typhoon Hagupit (2008) at a given wind speed, likely due to much rougher surface conditions surrounding the tower deployed in Typhoon Chanthu (2010). Furthermore, the DH is calculated using two different methods: (1) based on surface‐layer theory; and (2) based on the standard turbulent spectra method. It is found that the first method tends to overestimate the value of DH compared to the second method, and the overestimation of the DH by the first method is much smaller over rougher underlying surface than over the smoother underlying surface. Our analysis shows that the magnitude of the DH over land is as large as the sensible heat flux (~100 W/m²) previously observed over the ocean, which should not be neglected in numerical models simulating tropical cyclones during landfalls.

Given the success of 4D‐variational methods (4D‐Var) in numerical weather prediction, and recent efforts to merge ensemble Kalman filters with 4D‐Var, we revisit how one can use importance sampling and particle filtering ideas within a 4D‐Var framework. This leads us to variational particle smoothers (varPS) and we study how weight‐localization can prevent the collapse of varPS in high‐dimensional problems. We also discuss the relevance of (localized) weights in near‐Gaussian problems. We test our ideas on the Lorenz'96 model of dimensions n = 40, n = 400, and n = 2,000. In our numerical experiments the localized varPS does not collapse and yields results comparable to ensemble formulations of 4D‐Var, while tuned EnKFs and the local particle filter lead to larger estimation errors. Additional numerical experiments suggest that using localized weights may not yield significant advantages over unweighted or linearized solutions in near‐Gaussian problems.

The inner-core thermodynamic structure of Hurricane Edouard (2014) is explored, primarily through an examination of both high-altitude dropsondes deployed during NASA’s Hurricane and Severe Storm Sentinel (HS3) campaign and a 60-member convection-permitting ensemble initialized with an ensemble Kalman filter. The 7-day forecasts are initialized coincident with Edouard’s tropical depression designation and include Edouard’s significant intensification to a major hurricane. Ten-member ensemble groups are created based on timing of near rapid intensification (RI) onset, and the associated composite inner-core temperature structures are analyzed. It is found that at Edouard’s peak intensity, in both the observations and the simulations, the maximum inner-core perturbation temperature (~10–12 K) occurs in the mid-levels (~4–8 km). In addition, in all composite groups that significantly intensify, the evolution of the area-averaged inner-core perturbation temperatures indicate that weak to moderate warming (at most 4 K) begins to occur in the low- to mid-levels (~2–6 km) ~24–48 h prior to RI, and this warming significantly strengthens and deepens (up to ~8 km) ~24 h after RI has begun. Despite broad similarities in the evolution of Edouard’s warm core in these composites, variability in the height and strength of the maximum perturbation temperature and in the overall development of the inner-core temperature structure are present amongst the members of the composite groups (despite similar intensity time series). This result and concomitant correlation analyses suggest that the strength and height of the maximum perturbation temperature is not a significant causal factor for RI onset in this ensemble. Fluctuations in inner-core temperature structure occur either in tandem with or after significant intensity changes.

Real-time ensemble forecasts from the PSU WRF-EnKF system for Hurricane Joaquin (2015) are examined in this study. The ensemble forecasts from early in Joaquin’s lifecycle displayed large track spread, with nearly half of the ensemble members tracking Joaquin towards the United States east coast and the other half tracking Joaquin out to sea. The ensemble forecasts also displayed large intensity spread with many of the members developing into major hurricanes and other ensemble members not intensifying at all. Initial condition differences from the regions greater than (less than) 300 km were isolated by effectively removing initial condition differences in desired regions through relaxing each ensemble member to GFS (APSU) initial conditions. The regions of initial condition errors contributing to the track spread were examined, and the dominant source of track errors arose from the region greater than 300 km from the tropical cyclone center. Further examination of the track divergence revealed that the region between 600 and 900 km from the initial position of Joaquin was found to be the largest source of initial condition errors that contributed to this divergence. Small differences in the low-level steering flow, originating from perturbations between 600 and 900 km from the initial position, might have resulted in the bifurcation of the forecast tracks of Joaquin. The initial condition errors north of the initial position of Joaquin were also shown to contribute most significantly to the track divergence. The region inside of 300 km, specifically the initial intensity of Joaquin, was the dominant source of initial condition errors contributing to the intensity spread.

Severe weather events can have a significant impact on local communities due to the loss of life and property. Forecast busts associated with high-impact weather events have been attributed to initial condition errors over data sparse regions such as the Pacific Ocean. Numerous flight campaigns have found that targeted observations over these areas can improve forecasts. To better understand the impacts of measurement type and sampling domains on forecast performance, Observing System Simulation Experiments are performed using the National Centers for Environmental Prediction Global Forecast System (GFS) with Hybrid 3DEnVar data assimilation and the ECMWF T511 Nature Run. First, three types of simulated perfect dropsonde observations (temperature, specific humidity, and wind) are assimilated into the GFS system over a large idealized sampling domain covering the Pacific Ocean. For three winter storms studied, forecast error was found to be significantly reduced with all three types of measurements providing the most benefit (~ 5-15% reduction in error). Instances when forecasts are not improved are investigated and concluded to be due to challenging meteorological structures such as cutoff lows and interactions with atmospheric structures outside the sampling domain. Second, simulated dropsondes are assimilated over sensitive areas and flight tracks established using the Ensemble Transform Sensitivity (ETS) technique. For all three winter storms, forecast error is reduced up to 5%, which is less than that found using an idealized domain. These results suggest that targeted observations over the Pacific Ocean may provide a small improvement to winter storm forecasts over the United States.

The Fourth International Workshop on Tropical Cyclone Landfall Processes (IWTCLP-4) was held in Macao, China from 5-7 December 2017. The workshop was organized by the World Meteorological Organization (WMO) Expert Team on Tropical Cyclone Landfall Processes in partnership with the WMO Tropical Cyclone Program. The workshop provided a forum for discussion between researchers and forecasters on the current status of tropical cyclone landfall processes and on priorities and opportunities for research. More than 60 leading research scientists and warning specialists working on topics related to tropical cyclone landfall examined current knowledge, forecasting, and research trends from an integrated global perspective. The workshop offered a number of recommendations for future forecasting studies and research with special regard to the varying needs of different tropical cyclone affected regions. The recommendations emanating from the workshop will be presented at the upcoming Ninth International Workshop on Tropical Cyclones (IWTC-9) (Hawaii, USA, 3-7 December 2018).

Recently, the serial approach to solving the Square-Root Ensemble Kalman Filter (ESRF) equations in the presence of covariance localization was found to depend on the order of observations. As shown previously, correctly updating the localized posterior covariance in serial requires additional effort and computational expense. A recent work, Steward et al. (2017), details an all-at-once direct method to solve the ESRF equations in parallel. This method uses the eigenvectors and eigenvalues of the forward observation covariance matrix to solve the difficult portion of the ESRF equations. The remaining assimilation is easily parallelized, and the analysis does not depend on the order of observations. While this allows for long localization lengths that would render local analysis methods inefficient, in theory an eigenpair-based method scales as the cube number of observations, making it infeasible for large numbers of observations. In this work, we extend this method to use the theory of matrix functions to avoid eigenpair computations. The Arnoldi process is used to evaluate the covariance localized ESRF equations on the reduced-order Krylov subspace basis. This method is shown to converge quickly and apparently regains a linear scaling with the number of observations. The method scales similarly to the widely-used serial approach of Anderson and Collins (2007) in wall-time but not in memory usage. To improve the memory usage issue, this method potentially can be used without an explicit matrix. In addition, hybrid ensemble and climatological covariances can be incorporated.

This paper investigates the sensitivity of simulated hurricane intensity and structure to two planetary boundary layer (PBL) schemes in the Hurricane Weather and Research Forecast model including (1) the GFS scheme (control run) that uses the K-profile method to parameterize turbulent fluxes, and (2) the MYJ scheme that is based on a turbulent kinetic energy (TKE) budget for turbulent closure. Idealized simulations with these two PBL schemes show that the storm in the TKE run is stronger than that in the control run after 3 days into simulation. Multi-scale structures are evaluated and compared between the control and the TKE runs prior to the divergence of the model-simulated intensity to elucidate the mechanism underlying such a difference in the intensity between the two runs. It is found that the storm in the TKE run has (i) a shallower boundary layer with a stronger PBL inflow, (ii) stronger boundary layer convergence closer to the storm center, (iii) higher vorticity and inertial stability inside the RMW, (iv) stronger and deeper updrafts in regions further inward from the radius of maximum wind (RMW), and (v) more convective bursts located near the RMW as compared to the control run. Angular momentum budget analysis suggests that the convergence of angular momentum in the boundary layer is much stronger in the TKE run than in the control run, which is responsible for faster spin-up of the hurricane vortex in the TKE run.

This study analyzes the fast-response (20-Hz) wind data collected by a multi-level tower during the landfalls of Tropical Storm Lionrock (1006), Typhoon Fanapi (1011) and Typhoon Megi (1015) in 2010. Turbulent momentum fluxes are calculated using the standard eddy-correlation method. Vertical eddy diffusivity (K_m) and mixing length are estimated using the directly measured momentum fluxes and mean-wind profiles. It is found that the momentum flux increases with wind speed at all four levels. The eddy diffusivity calculated using the direct-flux method is compared to that using a theoretical method in which the vertical eddy diffusivity is formulated as a linear function of the friction velocity and height. It is found that below ~ 60 m, K_m can be approximately parameterized using this theoretical method, though this method overestimates K_m for higher altitude, indicating that the surface-layer depth is close to 60 m in the tropical cyclones studied here. It is also found that K_m at each level varies with wind direction during landfalls: K_m estimated based on observations with landward fetch is significantly larger than that estimated using data with seaward fetch. This result suggests that different parameterizations of K_m should be used in the boundary-layer schemes of numerical models forecasting tropical cyclones over land versus over the ocean.

This study evaluates the impact of assimilating high-resolution inner-core reconnaissance observations on tropical cyclone initialization and prediction in the 2013 version of the operational Hurricane Weather Research and Forecasting (HWRF) model. The 2013 HWRF data assimilation system is a GSI-based hybrid ensemble-variational system that in this study uses the Global Data Assimilation System ensemble to estimate flow-dependent background error covariance. Assimilation of inner-core observations improves track forecasts and reduces intensity error after 18-24 h. The positive impact on the intensity forecast is mainly found in weak storms, where inner-core assimilation produces more accurate tropical cyclone structures and reduces positive intensity bias. Despite such positive benefits, there is degradation in short-term intensity forecasts that is attributable to spin-down of strong storms, which has also been seen in other studies. There are several reasons for the degradation of intense storms. First, a newly-discovered interaction between model biases and the HWRF vortex initialization procedure causes the first-guess wind speed aloft to be too strong in the inner core. The problem worsens for the strongest storms, leading to a poor first-guess fit to observations. Though assimilation of reconnaissance observations results in analyses that better fit the observations, it also causes a negative intensity bias at the surface. In addition, the covariance provided by the NCEP global model is inaccurate for assimilating inner-core observations, and model physics biases result in a mismatch between simulated and observed structure. The model ultimately cannot maintain the analysis structure during the forecast, leading to spin-down.

GHOST would continuously monitor storm-induced gravity waves, observing their development through complete storm life-cycles in order to elucidate causal relationships between storm phenomena linked to latent heating and gravity-wave production. The prediction of tropical cyclone rapid intensification is one of the most pressing unsolved problems in hurricane forecasting. The signatures of gravity waves launched by strong convective updrafts are often clearly seen in airglow and carbon dioxide thermal emission spectra under favorable atmospheric conditions. By continuously monitoring the Atlantic hurricane belt from the main development region to the vulnerable sections of the continental U.S. at high cadence it will be possible to investigate the utility of storm-induced gravity wave observations for the diagnosis of impending storm intensification. Such a capability would also enable significant improvements in our ability to characterize the 3D, transient behavior of upper atmospheric gravity waves, and point the way to future observing strategies that could mitigate the risk to human life due to severe storms. This paper describes a new mission concept involving a mid-infrared imager hosted aboard a geostationary satellite positioned at approximately 80°W longitude. The sensor’s 3-km pixel size ensures that gravity wave horizontal structure is adequately resolved, while a 30-s refresh rate enables improved definition of the dynamic intensification process. In this way the transient development of gravity wave perturbations caused by both convective and cyclonic storms may be discerned in near real-time.

Using a combination of NOAA P-3 aircraft tail Doppler radar, NOAA and NASA dropsondes, and buoy and drifter based sea surface temperature data, different types of downdrafts and their influence on boundary layer (BL) thermodynamics are examined in Hurricane Earl (2010) during periods prior to rapid intensification (RI; a 30 knot increase in intensity over 24 hours) and during RI. Before RI, the BL was generally warm and moist. The largest hindrances for intensification are convectively driven downdrafts inside the radius of maximum winds (RMW) and upshear-right quadrant and vortex-tilt induced downdrafts outside the RMW in the upshear-left quadrant. Possible mechanisms for overcoming the low entropy (θ_e) air induced by these downdrafts are BL recovery through air-sea enthalpy fluxes and turbulent mixing by atmospheric eddies. During RI, convective downdrafts of varying strengths in the upshear-left quadrant had differing effects on the low-level entropy and surface heat fluxes. Interestingly, the stronger downdrafts corresponded with maximums in 10-m θ_e. It is hypothesized that the large amount of evaporation in a strong (>2 m s^-1) downdraft underneath a precipitation core can lead to high amounts of near-surface specific humidity. By contrast, weaker downdrafts corresponded with minimums in 10-m θ_e, likely because they contained lower evaporation rates. Since weak and dry downdrafts require more surface fluxes to recover the low entropy air than strong and moist downdrafts, they are greater hindrances to storm intensification. This study emphasizes how different types of downdrafts are tied to hurricane intensity change through their modification of BL thermodynamics.

The relationship between radial and azimuthal variations in the composite characteristics of convective bursts (CBs), i.e., regions of the most intense upward motion in tropical cyclones (TCs), and TC intensity change is examined using NOAA P-3 tail Doppler radar. Aircraft passes collected over a 13-year period are examined in a coordinate system rotated relative to the deep-layer vertical wind shear vector and normalized by the low-level radius of maximum winds (RMW). The characteristics of CBs are investigated to determine how the radial and azimuthal variations of their structures are related to hurricane intensity change. In general, CBs have elevated reflectivity just below the updraft axis, enhanced tangential wind below and radially outward of the updraft, enhanced vorticity near the updraft, and divergent radial flow at the top of the updraft. When examining CB structure by shear-relative quadrant, the downshear-right (upshear-left) region has updrafts at the lowest (highest) altitudes and weakest (strongest) magnitudes. When further stratifying by intensity change, the greatest differences are seen upshear. Intensifying storms have updrafts on the upshear side at a higher altitude and stronger magnitude than steady-state storms. This distribution provides a greater projection of diabatic heating onto the azimuthal mean, resulting in a more efficient vortex spin-up. For variations based on radial location, CBs located inside the RMW show stronger updrafts at a higher altitude for intensifying storms. Stronger and deeper updrafts inside the RMW can spin up the vortex through greater angular momentum convergence and a more efficient vortex response to the diabatic heating.

This technical note describes a modification of the boundary layer parameterization scheme in the Hurricane Weather Research and Forecasting (HWRF) model, which improves the simulations of low-level wind and surface inflow angle in the eyewall area and has been implemented in the HWRF system and used in the operational system since 2016. The modification is on an observation-based adjustment of eddy diffusivity previously implemented in the model. It is needed because the previous adjustment resulted in a discontinuity in the vertical distribution of eddy diffusivity near the surface-layer top, which increases the friction within the surface layer and compromises the surface-layer constant-flux assumption. The discontinuity affects the simulation of storm intensity and intensification, one of the main metrics of model performance, particularly in strong tropical cyclones. This issue is addressed by introducing a height-dependent adjustment so that the vertical profile of eddy diffusivity is continuous throughout the boundary layer. It is shown that the implementation of the modification results in low-level winds and surface inflow angles in the storm’s eyewall region closer to observations.

Climate observations are needed to address a large range of important societal issues including sea level rise, droughts, floods, extreme heat events, food security, and fresh water availability in the coming decades. Past, targeted investments in specific climate questions have resulted in tremendous improvements in issues important to human health, security, and infrastructure. However, the current climate observing system was not planned in a comprehensive, focused manner required to adequately address the full range of climate needs. A potential approach to planning the observing system of the future is presented in this paper. First, this paper proposes that priority be given to the most critical needs as identified within the World Climate Research Program as Grand Challenges. These currently include seven important topics: melting ice and global consequences; clouds, circulation and climate sensitivity; carbon feedbacks in the climate system; understanding and predicting weather and climate extremes; water for the food baskets of the world; regional sea-level change and coastal impacts; and near-term climate prediction. For each Grand Challenge, observations are needed for long-term monitoring, process studies and forecasting capabilities. Second, objective evaluations of proposed observing systems, including satellites, ground-based and in situ observations, as well as potentially new, unidentified observational approaches, can quantify the ability to address these climate priorities. And third, investments in effective climate observations will be economically important as they will offer a magnified return on investment that justifies a far greater development of observations to serve society’s needs.

A new remotely controlled AVAPS^® dropsonde system has been developed for and deployed on the NASA Global Hawk (GH) unmanned aircraft. Design, fabrication, and operation of the system was led by the National Center for Atmospheric Research (NCAR) with support from the National Oceanic and Atmospheric Administration (NOAA) Unmanned Aircraft Systems (UAS) program. The system has employed the NRD94 dropsonde, a smaller and lighter version of the standard RD94 dropsonde deployed from manned aircraft but with virtually identical sensors. The dropsondes provide in situ atmospheric profiles of temperature, pressure, and humidity at a 2 Hz data rate, and wind speed and direction at 4 Hz. The system is capable of carrying up to 90 dropsondes and can support 8 simultaneous soundings. Operation from the GH means that the dropsondes can be deployed from altitudes up to 19.8 km during flights in excess of 24-hour duration. Dropsonde launch is commanded directly by an operator on the ground in coordination with the aircraft commander. Over 2700 total dropsondes have been deployed from the GH during four major campaigns since 2011. Data are processed in near-real-time and have been employed by forecasters, for assimilation in numerical weather prediction models, and in diverse research studies. Intercomparison studies suggest the performance of the GH NRD94 dropsondes is similar to those deployed from manned aircraft. This paper describes the components and operation of the system and illustrates its unique capabilities through highlights of data application to research on the arctic atmosphere, atmospheric rivers, and tropical cyclones.

Improving physical parameterizations in forecast models is essential for hurricane prediction. This study documents the upgrade of horizontal diffusion parameterization in the Hurricane Weather Research and Forecasting (HWRF) model and evaluates the impact of this upgrade on hurricane forecasts. The horizontal mixing length (L_h) was modified based on aircraft observations and extensive idealized and real-case numerical experiments. Following Zhang and Marks (2015), who focused on understanding how the horizontal diffusion parameterization worked in HWRF and its dynamical influence on hurricane intensification using idealized simulations, a series of sensitivity experiments was conducted to simulate Hurricane Earl (2010) in which only L_h was varied. Results from the Earl forecasts confirmed the findings from previous theoretical and idealized numerical studies, in that both the simulated maximum intensity and intensity change rate are dependent on L_h. Comparisons between the modeled and observed structure of Hurricane Earl, such as storm size, boundary layer heights, warm-core height and temperature anomaly, and eyewall slope, suggested that the L_h used in the HWRF model should be decreased. Lowering L_h in HWRF has a positive impact on hurricane prediction based on over 200 retrospective forecasts of 10 Atlantic storms. Biases in both storm intensity and storm size are significantly reduced with the modified L_h.

This study presents a verification and an analysis of wind profile data collected during Tropical Storm Erika (2015) by a Doppler Wind Lidar (DWL) instrument aboard a P3 Hurricane Hunter aircraft of the National Oceanic and Atmospheric Administration (NOAA). DWL-measured winds are compared to those from nearly collocated GPS dropsondes and show good agreement in terms of both the wind magnitude and asymmetric distribution of the wind field. A comparison of the DWL-measured wind speeds versus dropsonde-measured wind speeds yields a reasonably good correlation (r² = 0.95), with a root mean square error (RMSE) of 1.58 m s⁻¹ and a bias of −0.023 m s⁻¹. Our analysis shows that the DWL complements the existing P3 Doppler radar, in that it collects wind data in rain-free and low-rain regions where Doppler radar is limited for wind observations. The DWL observations also complement dropsonde measurements by significantly enlarging the sampling size and spatial coverage of the boundary layer winds. An analysis of the DWL wind data shows that the boundary layer of Erika was much deeper than that of a typical hurricane-strength storm. Streamline and vorticity analyses based on DWL wind observations explain why Erika maintained intensity in a sheared environment. This study suggests that DWL wind data are valuable for real-time intensity forecasts, basic understanding of the boundary layer structure and dynamics, and offshore wind energy applications under tropical cyclone conditions.

The anomalous phenomena induced by the prevailing swell at low wind speeds prevent a complete understanding of air–sea interaction processes. Many studies have considered this complex problem, but most have focused on near-neutral conditions. In this study, the influence of the swell on the atmospheric boundary under nonneutral conditions was addressed by extending the turbulent closure models of Makin and Kudryavtsev and the Monin–Obukhov similarity theory (MOST; Monin and Yaglom) to the existence of swell and nonneutral conditions. It was shown that wind profiles derived from these models were consistent with each other and both departed from the traditional MOST. At low wind speeds, a supergeostrophic jet appeared on the upper edge of the wave boundary layer, which was also reported in earlier studies. Under nonneutral conditions, the influence of buoyancy was significant. The slope of the wind profile increased under stable conditions and became smoother under unstable conditions. Considering the effects of buoyancy and swell, the wind stress derived from the model agreed quantitatively with the observations.

During a routine penetration into Hurricane Felix late on 2 September 2007, NOAA-42 encountered extreme turbulence and graupel, flight-level horizontal wind gusts of over 83 m s^-1, and vertical wind speeds varying from 10 m s^-1 downward to 31 m s^-1 upward and back to nearly 7 m s^-1 downward within 1 min. This led the plane to rise nearly 300 m and then return to its original level within that time. Though a dropwindsonde was released during this event, the radars and data systems on board the aircraft were rendered inoperable, limiting the amount of data obtained. The feature observed during the flight is shown to be similar to that encountered during flights into Hurricanes Hugo (1989) and Patricia (2015), and by a dropwindsonde released into a misovortex in Hurricane Isabel (2014). This paper describes a unique dataset of a small-scale feature that appears to be prevalent in very intense tropical cyclones, providing new evidence for eye-eyewall mixing processes that may be related to intensity change.

Current practice is to transmit dropwindsonde data from aircraft using the TEMP-DROP format, which provides only the release location and time with 0.1° latitude-longitude (about 11 km), and 1-h resolutions, respectively. The current dropwindsonde has a fall speed of approximately 15 ms^-1, so the instrument will be advected faster horizontally than it will descend if the wind speed exceeds this value. Where wind speeds are greatest, such as in tropical cyclones, this will introduce large errors in the location of the observations, especially near the surface. A technique to calculate the correct time and location of each observation in the TEMP-DROP message is introduced. Mean differences between the calculated and reported locations are about 0.5 km for distance and 15 sec for time, or <1% of the error size for distance and <10% for time.

A new vortex-scale initialization scheme is presented for idealized coupled hurricane simulations. The atmospheric scheme involves construction of azimuthally averaged kinematic and thermodynamic initial fields based on historical composite datasets from hurricane reconnaissance aircraft. For ocean initialization, a statistical scheme is proposed to construct regression models among atmospheric and ocean fields in the hurricane inner core. For the numerical model, the Hurricane Weather Research and Forecasting (HWRF) model coupled with a one-dimensional, diffusive ocean model is used with modifications to initialize with the observation-based vortex and to ensure that the storm environment remains approximately steady. The primary goal in these simulations is to obtain steady-state hurricanes of category-1 intensity with characteristics typically observed during the hurricane season of the western Atlantic and Caribbean Sea regions. It is demonstrated that this is successfully achieved in the simulations. In an azimuthally averaged sense, regression models are found to capture about 70% of total variance for sea-surface temperature cooling and up to 55% of total variance for mixed-layer depth perturbation in the hurricane inner core. Furthermore, within the inner core of a hurricane vortex, it is found that storm speed contributes most to upper-ocean perturbations, whereas characteristics of the atmospheric vortex contribute very little. The importance of storm speed in controlling upper-ocean perturbations is strongest near the storm center, diminishing gradually toward no measurable impact beyond the immediate inner core.

The West African monsoon (WAM) and its landmark features, which include African easterly waves (AEWs) and the African easterly jet (AEJ), exhibit significant intraseasonal variability in boreal summer. However, the degree to which this variability is modulated by external large-scale phenomena, such as the Madden-Julian oscillation (MJO), remains unclear. The Weather Research and Forecasting (WRF) Model is employed to diagnose the importance of the MJO and other external influences for the intraseasonal variability of the WAM and associated AEW energetics by removing 30-90-day signals from initial and lateral boundary conditions in sensitivity tests. The WAM produces similar intraseasonal variability in the absence of external influences, indicating that the MJO is not critical to produce WAM variability. In control and sensitivity experiments, AEW precursor signals are similar near the AEJ entrance in East Africa. For example, an eastward extension of the AEJ increases barotropic and baroclinic energy conversions in East Africa prior to a 30-90-day maximum of perturbation kinetic energy in West Africa. The WAM appears to prefer a faster oscillation when MJO forcing is removed, suggesting that the MJO may serve as a pacemaker for intraseasonal oscillations in the WAM. WRF results show that eastward propagating intraseasonal signals (e.g., Kelvin wave fronts) are responsible for this pacing, while the role of westward propagating intraseasonal signals (e.g., MJO-induced Rossby waves) appears to be limited. Mean state biases across the simulations complicate the interpretation of results.

The Hurricane Weather Research and Forecasting model (HWRF) is a dynamical model that has shown annual improvements to its tropical cyclone (TC) track forecasts as a result of various modifications. This study focuses on an experimental version of HWRF, called the “basin-scale” HWRF (HWRF-B), configured with: (1) a large, static outer domain to cover multiple TC basins; and (2) multiple sets of high-resolution movable nests to produce forecasts for several TCs simultaneously. Although HWRF-B and the operational HWRF produced comparable average track errors for the 2011-2014 Atlantic hurricane seasons, strengths of HWRF-B are identified and linked to its configuration differences. HWRF-B track forecasts were generally more accurate compared to the operational HWRF when at least one additional TC was simultaneously active in the Atlantic or East Pacific basins and, in particular, when additional TCs were greater than 3500 km away. In addition, at long lead times, HWRF-B average track errors were lower than for the operational HWRF for TCs initialized north of 25°N or west of 60°W, highlighting the sensitivity of TC track forecasts to the location of the operational HWRF outermost domain. A case study, performed on Hurricane Michael, corroborated these HWRF-B strengths. HWRF-B shows potential to serve as an effective bridge between regional modeling systems and next generational global efforts.

One of the most important applications of a space-based Doppler Wind Lidar (DWL) would be to improve atmospheric analyses and weather forecasting. Since the mid-1980s, Observing System Simulation Experiments (OSSEs) have been conducted to evaluate the potential impact of space-based DWL data on numerical weather prediction (NWP). All of these OSSEs have shown significant beneficial impact on global analyses and forecasts. In more recent years, a limited number of experiments have been conducted to evaluate the potential impact of DWL data on hurricane forecasting and also to begin to evaluate the impact of real airborne DWL observations. These latest studies suggest that DWL can complement existing hurricane observations effectively and have the potential to contribute to improved hurricane track and intensity forecasting.

A method to simulate characteristics of wind speed in the boundary layer of tropical cyclones in an idealized manner is developed and evaluated. The method can be used in a single-column modelling set-up with a planetary boundary-layer parametrization or within large-eddy simulations (LES). The key step is to include terms in the horizontal velocity equations representing advection and centrifugal acceleration in tropical cyclones that occur on scales larger than the domain size. Compared to other recently developed methods, which require two input parameters (a reference wind speed and radius from the centre of a tropical cyclone), this new method also requires a third input parameter: the radial gradient of reference wind speed. With the new method, simulated wind profiles are similar to composite profiles from dropsonde observations; in contrast, a classic Ekman-type method tends to overpredict inflow-layer depth and magnitude, and two recently developed methods for tropical cyclone environments tend to overpredict near-surface wind speed. When used in LES, the new technique produces vertical profiles of total turbulent stress and estimated eddy viscosity that are similar to values determined from low-level aircraft flights in tropical cyclones. Temporal spectra from LES produce an inertial subrange for frequencies ≳0.1 Hz, but only when the horizontal grid spacing ≲20 m.

The impact of Global Hawk dropwindsondes on tropical cyclone analyses and forecasts is evaluated in an ensemble-based vortex-scale data assimilation system. Two cases from Hurricane Edouard (2014) are presented. In the first case, inner-core observations were exclusively provided by Global Hawk (GH) dropwindsondes, while in the second case, GH dropwindsondes were concentrated in the storm’s near environment and were complemented by an extensive number of inner-core observations from other aircraft. It is found that when GH dropwindsondes are assimilated, a positive impact on the minimum sea-level pressure (MSLP) forecast persists for most lead times in the first case, conceivably due to the better representation of the initial vortex structure, such as the warm-core anomaly and primary and secondary circulations. The verification of the storm’s kinematic and thermodynamic structure in the forecasts of the first case is carried out relative to the time of the appearance of a secondary wind maximum (SWM) using the tail Doppler radar and dropwindsonde composite analyses. A closer-to-observed wavenumber-zero wind field in the experiment with GH dropwindsondes is seen before the SWM is developed, which likely contributes to the superior intensity forecast up to 36 h. The improvement in the warm-core anomaly in the forecasts from the experiment with GH dropwindsondes is believed to have also contributed to the consistent improvement in the MSLP forecast. For the latter case, a persistent improvement in the track forecast is seen, which is consistent with a better representation of the near-environmental flow obtained from GH data in the same region.

The mainstay of the global Radio Occultation (RO) system, the COSMIC constellation of six satellites launched in April 2006, is already past the end of its nominal lifetime and the number of soundings are rapidly declining because the constellation is degrading. For about the last decade, COSMIC profiles have been collected and their retrievals assimilated in numerical weather prediction systems to improve operational weather forecasts. The success of RO in increasing forecast skill and COSMIC’s aging constellation have motivated planning for the COSMIC-2 mission, a 12-satellite constellation to be deployed in two launches. The first six satellites (COSMIC-2A) are expected to be deployed in December 2017 in a low-inclination orbit for dense equatorial coverage, while the second six (COSMIC-2B) are expected to be launched later in a high inclination orbit for global coverage. In order to evaluate the potential benefits from COSMIC-2, we have used an earlier version of the NCEP’s operational forecast model and data assimilation system to conduct a series of Observing System Simulation Experiments with simulated soundings from the COSMIC-2 mission. In agreement with earlier studies using real RO observations, the benefits from assimilating COSMIC-2 observations are found to be most significant in the Southern Hemisphere. No or very little gain in forecast skill is found by adding COSMIC-2A to COSMIC- 2B, making the launch of COSMIC-2B more important for terrestrial global weather forecasting than that of COSMIC-2A. Furthermore, results suggest that further improvement in forecast skill might better be obtained with the addition of more RO observations with global coverage and other types of observations.

Two eyewall replacement cycles were observed in Hurricane Gonzalo by the NOAA P3 tail radar and the recently developed NASA HIWRAP radar. These observations captured detailed precipitation and kinematic features of Gonzalo’s concentric eyewalls both before and after the outer eyewall’s winds became the vortex maximum winds. The data were analyzed relative to the deep-layer environmental wind shear vector. During the beginning eyewall replacement cycle stages, the inner and outer eyewalls exhibited different asymmetries. The inner eyewall asymmetry exhibited significant low-level inflow, updrafts, and positive tangential acceleration in the downshear quadrants, consistent with observational and theoretical studies. The outer eyewall asymmetry exhibited these features in the left-of-shear quadrants, further downwind from those of the inner eyewall. It is suggested that the low-level inflow occurring at the outer but not at the inner eyewall in the downwind regions signals a barrier effect that contributes to the eventual decay of the inner eyewall. Toward the later eyewall replacement stages, the outer eyewall asymmetry shifts upwind, becoming more aligned with the asymmetry of the earlier inner eyewall. This upwind shift is consistent with the structural evolution of eyewall replacement as the outer eyewall transitions into the primary eyewall of the storm.

Tropical cyclone (TC) outflow and its relationship to TC intensity change and structure were investigated in the Office of Naval Research Tropical Cyclone Intensity (TCI) field program during 2015 using dropsondes deployed from the innovative new High-Definition Sounding System (HDSS) and remotely sensed observations from the Hurricane Imaging Radiometer (HIRAD), both on board the NASA WB-57 that flew in the lower stratosphere. Three noteworthy hurricanes were intensively observed with unprecedented horizontal resolution: Joaquin in the Atlantic and Marty and Patricia in the eastern North Pacific. Nearly 800 dropsondes were deployed from the WB-57 flight level of ∼60,000 ft (∼18 km), recording atmospheric conditions from the lower stratosphere to the surface, while HIRAD measured the surface winds in a 50-km-wide swath with a horizontal resolution of 2 km. Dropsonde transects with 4–10-km spacing through the inner cores of Hurricanes Patricia, Joaquin, and Marty depict the large horizontal and vertical gradients in winds and thermodynamic properties. An innovative technique utilizing GPS positions of the HDSS reveals the vortex tilt in detail not possible before. In four TCI flights over Joaquin, systematic measurements of a major hurricane’s outflow layer were made at high spatial resolution for the first time. Dropsondes deployed at 4-km intervals as the WB-57 flew over the center of Hurricane Patricia reveal in unprecedented detail the inner-core structure and upper-tropospheric outflow associated with this historic hurricane. Analyses and numerical modeling studies are in progress to understand and predict the complex factors that influenced Joaquin’s and Patricia’s unusual intensity changes.

Extratropical transition (ET) is the process by which a tropical cyclone, upon encountering a baroclinic environment and reduced sea surface temperature at higher latitudes, transforms into an extratropical cyclone. ET is influenced by, and influences, phenomena from the tropics to the midlatitudes and from the meso- to the planetary-scales to extents that vary between individual events. Motivated in part by recent high-impact and/or extensively observed events such as North Atlantic Hurricane Sandy in 2012 and Western North Pacific Typhoon Sinlaku in 2008, this review details advances in understanding and predicting ET since the publication of an earlier review in 2003. Methods for diagnosing ET in reanalysis, observational, and model-forecast datasets are discussed. New climatologies for the eastern North Pacific and southwest Indian Oceans are presented alongside updates to western North Pacific and North Atlantic Ocean climatologies. Advances in understanding and, in some cases, modeling the direct impacts of ET-related wind, waves, and precipitation are noted. Improved understanding of structural evolution throughout the transformation stage of ET fostered in large part by novel aircraft observations collected in several recent ET events is highlighted. Predictive skill for operational and numerical model ET-related forecasts is discussed along with environmental factors influencing post-transition cyclone structure and evolution. Operational ET forecast and analysis practices and challenges are detailed. In particular, some challenges of effective hazard communication for the evolving threats posed by a tropical cyclone during and after transition are introduced. This review concludes with recommendations for future work to further improve understanding, forecasts, and hazard communication.

The tropical Atlantic basin is one of seven global regions where tropical cyclones (TCs) commonly originate, intensify, and affect highly populated coastal areas. Under appropriate atmospheric conditions, TC intensification can be linked to upper-ocean properties. Errors in Atlantic TC intensification forecasts have not been significantly reduced during the last 25 years. The combined use of in situ and satellite observations, particularly of temperature and salinity ahead of TCs, has the potential to improve the representation of the ocean, more accurately initialize hurricane intensity forecast models, and identify areas where TCs may intensify. However, a sustained in situ ocean observing system in the tropical North Atlantic Ocean and Caribbean Sea dedicated to measuring subsurface temperature, salinity, and density fields in support of TC intensity studies and forecasts has yet to be designed and implemented. Autonomous and Lagrangian platforms and sensors offer cost-effective opportunities to accomplish this objective. Here, we highlight recent efforts to use autonomous platforms and sensors, including surface drifters, profiling floats, underwater gliders, and dropsondes, to better understand air-sea processes during high-wind events, particularly those geared toward improving hurricane intensity forecasts. Real-time data availability is key for assimilation into numerical weather forecast models.

Ocean fields that initialize coupled TC prediction models must accurately represent the dynamics of mesoscale features and the associated distribution of upper ocean temperature and salinity. They must also provide unbiased realizations of upper ocean heat content and stratification. Ocean Observing System Simulation Experiments (OSSEs) are performed for three storms: Isaac, 2012; Edouard, 2014; and Gonzalo, 2014. These OSSEs assess the impact of rapid-response prestorm ocean profile surveys on improving ocean model initialization. Two types of surveys are evaluated: airborne deployments of expendable profilers and deployments of in situ thermistor chains along lines intersecting predicted storm paths. Assimilation of the existing ocean observing system substantially constrains mesoscale structure in dynamical fields, primarily because of the four available altimeters. However, these observations only modestly constrain mesoscale structure and bias in upper ocean thermal fields. Adding rapid-response airborne surveys to these observing systems produces substantial additional correction in thermal fields, but minimal additional correction in dynamical fields. Without altimetry assimilation, rapid-response profiles produce large additional correction in both dynamical and thermal fields. Airborne CTDs sampling temperature and salinity over 1000 m versus XBTs sampling temperature over 400 m produce additional correction for dynamical fields, but not for upper ocean thermal fields. Airborne surveys are generally more effective than thermistor chain deployments because they can sample a larger area at higher horizontal resolution and because the latter only measures temperature over the upper ∼100 m. Both airborne profile surveys and thermistor chain deployments effectively reduce upper ocean thermal biases.

Observing System Simulated Experiments (OSSEs) performed during the 2014 North Atlantic hurricane season quantify ocean observing system impacts with respect to improving ocean model initialization in coupled tropical cyclone (TC) prediction systems. The suitability of the OSSE system forecast model (FM) with respect to the previously validated Nature Run is demonstrated first. Analyses are then performed to determine the calibration required to obtain credible OSSE impact assessments. Impacts on errors and biases in fields important to TC prediction are first quantified for three major components of the existing operational ocean observing system. Satellite altimetry provides the greatest positive impact, followed by Argo floats and sea surface temperature measurements from both satellite and in-situ systems. The OSSE system is then used to investigate observing system enhancements, specifically regional underwater glider deployments during the 2014 hurricane season. These deployments resulted in modest positive impacts on ocean analyses that were limited by (1) errors in the horizontal structure of the increment field imposed by individual gliders and (2) memory loss in the spreading of these corrections by nonlinear model dynamics. The high-resolution, three-dimensional representation of the truth available in OSSE systems allows these issues to be studied without high-density ocean observations.

This paper investigates convective burst (CB) evolution in Weather Research and Forecasting (WRF) simulations of two tropical cyclones (TCs), focusing on the relationship between CBs and TC intensity change. Analysis of intensity change in the simulations shows that there are more CBs inside the radius of maximum winds (RMW) during times when the TCs are about to intensify, while weakening/steady times are associated with more CBs outside the RMW, consistent with past observational and theoretical studies. The vertical mass flux distributions show greater vertical mass flux at upper levels both from weaker updrafts and CBs for intensifying cases. The TC simulations are further dissected by past intensity change, and times of sustained intensification have more CBs than times when the TC has been weakening but then intensifies. This result suggests that CB development may not always be predictive of intensification, but rather may occur as a result of ongoing intensification and contribute to ongoing intensification. Abrupt short-term intensification is found to be associated with an even higher density of CBs inside the RMW than slower intensification. Lag correlations between CBs and intensity reveal a broad peak, with the CBs leading pressure falls by 0-3 hours. These relationships are further confirmed by analysis of individual simulation periods, although the relationship can vary depending on environmental conditions and the previous evolution of the TC. These results show that increased convection due to both weak updrafts and CBs inside the RMW are favorable for sustained TC intensification, and show many details of the typical short-term response of the TC core to CBs.

Understanding the structure and evolution of the tropical cyclone (TC) inner core remains an elusive challenge in tropical meteorology, especially the role of transient asymmetric features such as localized strong updrafts known as convective bursts (CBs). This study investigates the formation of CBs and their role in TC structure and evolution using high-resolution simulations of two Atlantic hurricanes (Dean 2007 and Bill, 2009) with the Weather Research and Forecasting (WRF) model. Several different aspects of the dynamics and thermodynamics of the TC inner-core region are investigated with respect to their influence on TC convective burst development. Composites with CBs show stronger radial inflow in the lowest 2 km, and stronger radial outflow from the eye to the eyewall around z = 2‑4 km, than composites without CBs. Asymmetric vorticity associated with eyewall mesovortices appears to be a major factor in leading to some of the radial flow anomalies that lead to CB development. The anomalous outflow from these mesovortices, along with outflow from supergradient parcels above the boundary layer, favors low-level convergence and also appears to mix high-θ_e air from the eye into the eyewall. Analysis of individual CBs and parcel trajectories show that parcels are pulled into the eye, and briefly mix with the eye air. The parcels then rapidly move outward into the eyewall, and quickly ascend in CBs, in some cases with vertical velocity over 20 ms^-1. These results support the importance of horizontal asymmetries in forcing extreme asymmetric vertical velocity in tropical cyclones.

The empirical cumulative density function (ECDF) approach can be used to combine multiple, diverse assessment metrics into summary assessment metrics (SAMs) to analyze the results of impact experiments and pre-operational implementation testing with numerical weather prediction (NWP) models. The main advantages of the ECDF approach are that it is amenable to statistical significance testing and produces results that are easy to interpret because the SAMs for various subsets tend to vary smoothly and in a consistent manner. In addition, the ECDF approach can be applied in various contexts thanks to the flexibility allowed in the definition of the reference sample. The interpretations of the examples presented here of the impact of potential future data gaps are consistent with previously reported conclusions. An interesting finding is that the impact of observations decreases with increasing forecast time. This is interpreted as being caused by the masking effect of NWP model errors increasing to become the dominant source of forecast error.

In the last few years there has been tremendous improvement in the calibration of ocean surface vector winds from scatterometers and polarimetric radiometers. This is the first detailed investigation of across-swath consistency in scatterometer-derived (i.e., QSCAT, ASCAT-A, OSCAT, and ASCAT-B) vorticity (curl of the ocean surface vector winds). Spatial derivatives of the wind fields are very important for atmospheric boundary-layer processes, upper ocean forcing, and deep ocean forcing. Improvements in wind calibration imply improvements in derivatives of these winds; however, it does not imply consistency. This study demonstrates near consistency in across-swath vorticity and near consistency between platforms.

Synthetic aperture radar (SAR), with its high spatial resolution, large areal coverage, day/night imaging capability, and penetrating cloud capability has been used as an important tool for tropical cyclone monitoring. The accuracy of locating tropical cyclone centers has a large impact on the accuracy of tropical cyclone track prediction. This study focuses on the center location of tropical cyclones in SAR images. Based on an analysis of the characteristics of tropical cyclone SAR images, combined with the theory and methods of SAR image segmentation and computer vision, center location methods for both tropical cyclones with eyes in SAR images and tropical cyclones without eyes in SAR images are presented in this chapter. The main work is as follows: (1) For a tropical cyclone with its eye in the SAR image, the eye area in the image appears as black or dark gray for there being no rain and little wind in the eye area. However, the gray level contrast is not always obvious. There may be no complete or clear eye when a tropical cyclone is in the development period or the recession period. The eye area in a tropical cyclone SAR image may appear as a light gray area at these periods. It is, therefore, necessary to enhance the gray level contrast before image segmentation. Additionally, denoising the speckle noise is also necessary for SAR image processing. A tropical cyclone eye extraction method based on a non-local means method and labeled watershed algorithm is given. A PPB filter is used to denoise the speckle noise. The top-hat transform is then used to enhance the contrast. Finally, the tropical cyclone eye is extracted by the labeled watershed algorithm. The eye area extracted with this method is computed to compare it with the eye area extracted manually. The comparison indicates the accuracy of the extraction accuracy. (2) Generally speaking, the center of the tropical cyclone without its eye is located with the template matching method for a single image. The spiral cloud band of the tropical cyclone without its eye is information that can be fully used in the tropical cyclone SAR image. By taking advantage of the simple background with little textural information, a center location method of the tropical cyclone without its eye in the SAR image based on feature learning and visual saliency detection is proposed. Spiral cloud bands appear as light and dark spiral structures in tropical cyclone SAR images, containing rich directional information. Therefore, a salient region map that takes advantage of the gray contrast feature and orientation feature is built. The salient region map makes the spiral cloud bands outstanding and excludes the irrelevant clouds. The morphology method is then used to extract the spiral bands in the salient region map, and the skeleton lines of spiral cloud bands are extracted. Finally, the tropical cyclone center is estimated with the inflow angle model and the particle swarm optimization algorithm. The estimation results are compared with the best track data, confirming the validity of the algorithm.

Spaceborne microwave synthetic aperture radar (SAR), with its high spatial resolution, large area coverage, day/night imaging capability, and penetrating cloud capability, has been used as an important tool for tropical cyclone monitoring. The accuracy of locating tropical cyclone centers has a large impact on the accuracy of tropical cyclone track prediction. Usually, the center of a tropical cyclone can be accurately located if the tropical cyclone eye is fully covered by a SAR image. In some cases, due to the limited coverage of the SAR, only a part of a tropical cyclone can be imaged without the eye. From a SAR image processing point of view, these facts make the automatic center location of tropical cyclones a challenging work. This paper addresses the problem by proposing a semiautomatic center location method based on salient region detection and pattern matching. A salient region detection algorithm is proposed, in which the salient region map contains mainly the rain bands of a tropical cyclone in a SAR image. The pattern matching problem is transformed into an optimization problem solved by using the particle swarm optimization algorithm to search for the best estimated center of a tropical cyclone. To estimate the accuracy of the located center, we compare the results with the NOAA-National Hurricane Center's best track data. Experiments demonstrate that the proposed method achieves good accuracy for locating the centers of tropical cyclones from SAR images that do not contain a distinguishable eye signature.

Dual-polarization scanning radar measurements, air temperature soundings, and a polarimetric radar-based particle identification scheme are used to generate maps and probability density functions (PDFs) of the ice water path (IWP) in Hurricanes Arthur (2014) and Irene (2011) at landfall. The IWP is separated into the contribution from small ice (i.e., ice crystals), termed small-particle IWP, and large ice (i.e., graupel and snow), termed large-particle IWP. Vertically profiling radar data from Hurricane Arthur suggest that the small ice particles detected by the scanning radar have fall velocities mostly greater than 0.25 m s^-1 and that the particle identification scheme is capable of distinguishing between small and large ice particles in a mean sense. The IWP maps and PDFs reveal that the total and large-particle IWPs range up to 10 kg m^-2, with the largest values confined to intense convective precipitation within the rainbands and eyewall. Small-particle IWP remains mostly < 4 kg m^-2, with the largest small-particle IWP values collocated with maxima in the total IWP. PDFs of the small-to-total IWP ratio have shapes that depend on the precipitation type (i.e., intense convective, stratiform, or weak echo precipitation). The IWP ratio distribution is narrowest (broadest) in intense convective (weak echo) precipitation and peaks at a ratio of about 0.1 (0.3).

Because surface wind speeds within tropical cyclones are important for operational and research interests, it is vital to understand surface wind structure in relation to various storm and environmental influences. In this study, global rain-corrected scatterometer winds are used to quantify and evaluate characteristics of tropical cyclone surface wind asymmetries using a modified version of a proven aircraft-based low wavenumber analysis tool. The globally expanded surface wind dataset provides an avenue for a robust statistical analysis of the changes in structure due to tropical cyclone intensity, deep-layer vertical wind shear, and wind shear’s relationship with forward storm motion. A presentation of the quantified asymmetry indicates that wind shear has a significant influence on tropical storms at all radii but only for areas away from the radius of maximum wind in both non-major and major hurricanes. Evaluation of shear’s directional relation to motion indicates that a cyclonic rotation of the surface wind field asymmetry from downshear-left to upshear-left occurs in conjunction with an anticyclonic rotation of the directional relationship (i.e., from shear direction to the left, same, right, or opposite of the motion direction). It was discovered that in tropical cyclones experiencing effects from wind shear, an increase of absolute angular momentum transport occurs downshear and often downshear-right. The surface wind speed low wavenumber maximum in turn forms downwind of this momentum transport.

Global navigation satellite system (GNSS) radio occultations (RO) over the last 10 years have proved to be a valuable and essentially unbiased data source for operational global numerical weather prediction. However, the existing sampling coverage is too sparse in both space and time to support forecasting of severe mesoscale weather. In this study, the case study or quick observing system simulation experiment (QuickOSSE) framework is used to quantify the impact of vastly increased numbers of GNSS RO profiles on mesoscale weather analysis and forecasting. Our study focuses on a severe convective weather event that produced both a tornado and flash flooding in Oklahoma on May 31, 2013. The WRF model is used to compute a realistic and faithful depiction of reality. This 2-km “nature run” (NR) serves as the “truth” in our study. The NR is sampled by two proposed constellations of GNSS RO receivers that would produce 250 thousand and 2.5 million profiles/day globally. These data are then assimilated using WRF and a 24-member, 18-km-resolution, physics-based ensemble Kalman filter. The data assimilation is cycled hourly and makes use of a non-local, excess phase observation operator for RO data. The assimilation of greatly increased numbers of RO profiles produces improved analyses, particularly of the lower tropospheric moisture fields. The forecast results suggest positive impacts on convective initiation. Additional experiments should be conducted for different weather scenarios and with improved OSSE systems.

An efficient radiative transfer model has been developed for hyperspectral infrared radiance simulation under both clear- and cloudy-sky conditions. The hyperspectral IR cloudy radiative transfer model (HIRTM) combines atmospheric transmittances due to molecular absorption and cloud absorption and scattering from cloud hydrometeors. An efficient analytical Jacobian methodology is also developed under both clear- and cloudy-sky conditions, which is needed both to assimilate cloudy radiances directly into numerical weather prediction models and to retrieve atmospheric soundings and cloud properties simultaneously from cloudy radiance measurements. In comparing HIRTM and its analytical Jacobian with the community radiative transfer model (CRTM), our research has shown that HIRTM's Jacobian calculations are similar to those of CRTM. HIRTM and CRTM synthetic observations derived from model output are compared with corresponding real observations from Geostationary Operational Environmental Satellite 13 Imager observations, and both perform similarly under water clouds, while CRTM is colder than HIRTM for thick ice clouds.

A comprehensive examination of tropical cyclone (TC) kinematic and thermodynamic structure in the Atlantic basin is created from the Extended Flight Level Dataset (FLIGHT+) for Tropical Cyclones (Version 1.1). In situ data collected at the 700-hPa flight level by NOAA WP-3D and USAF WC-130 aircraft from 1999 to 2012 are analyzed. A total of 233 azimuthal mean profiles comprised of 1498 radial legs are stratified by TC intensity and 12-hour intensity change. A matrix of composite structures is created for minor (Category 1 and 2) and major (Category 3 and above) hurricanes that are intensifying [intensity increase ≥ 10 kt (12 h)⁻¹], steady-state [intensity change between ± 5 kt (12 h)⁻¹], and weakening [intensity decrease ≤ − 10 kt (12 h)⁻¹. Additional considerations to the impacts of age on TC structure are given as well. Axisymmetric radial composites reveal that intensifying TCs have statistically significant structural differences from TCs that are steady-state or weakening, but that these differences also depend on the intensity of the TC. Intensifying TCs (both minor and major hurricanes) are characterized by steep tangential wind gradients radially inward of the radius of maximum tangential wind (RMW) that contributes to a ring-like structure of vorticity and inertial stability. Tangential wind structural differences are more pronounced in the eye of minor hurricanes compared to major hurricanes. Intensifying TCs are found to have higher inner and outer-core moisture compared to steady-state and weakening TCs. Furthermore, intensifying major hurricanes possess drier eyes compared to steady-state and weakening major hurricanes.

The impact of assimilating ocean surface wind observations from the Cyclone Global Navigation Satellite System (CYGNSS) is examined in a high-resolution Observing System Simulation Experiment (OSSE) framework for tropical cyclones (TCs). CYGNSS is a planned National Aeronautics and Space Administration constellation of microsatellites that utilizes existing GNSS satellites to retrieve surface wind speed. In the OSSE, CYGNSS wind speed data are simulated using output from a “nature run” as truth. In a case study using the regional Hurricane Weather Research and Forecasting modeling system and the Gridpoint Statistical Interpolation data assimilation scheme, analyses of TC position, structure, and intensity, together with large-scale variables, are improved due to the assimilation of the additional surface wind data. These results indicate the potential importance of CYGNSS ocean surface wind speed data and furthermore that the assimilation of directional information would add further value to TC analyses and forecasts.

Prior studies have shown an association between symmetrically-distributed precipitation and tropical cyclone (TC) intensification. Although environmental vertical wind shear typically forces an asymmetric precipitation distribution in TCs, the magnitude of this asymmetry can exhibit considerable variability, even among TCs that experience similar shear magnitudes. This observational study examines the thermodynamic and kinematic influences on precipitation symmetry in two such cases, Bertha and Cristobal (2014). Consistent with the impact of the shear, both TCs exhibited a tilted vortex, as well as a pronounced azimuthal asymmetry, with the maximum precipitation occurring in the downshear-left quadrant. However, Bertha was characterized by more symmetrically distributed precipitation and relatively modest vertical motions, while Cristobal was characterized by more azimuthally confined precipitation and much more vigorous vertical motions. Observations showed three potential hindrances to precipitation symmetry that were more prevalent in Cristobal than in Bertha: (i) Convective downdrafts that transported low entropy air downwards into the boundary layer, cooling and stabilizing the lower troposphere downstream in the left of shear and upshear quadrants; (ii) Subsidence in the upshear quadrants, which acted to increase the temperature and decrease the relative humidity of the mid-troposphere, resulting in capping of the boundary layer; and (iii) Lateral advection of mid-tropospheric dry air from the environment, which dried the TC’s upshear quadrants.

Internal gravity waves are continuously generated by deep moist convection around the globe. Satellite images suggest that tropical cyclones produce short-wavelength, high-frequency waves that radiate outward, with the wave fronts wrapped into tight spirals by the large differential advection of the sheared tangential flow. This letter presents new in situ observations of such waves from two sources: flight level data from research aircraft that show radial wavelengths of 2–10 km and vertical velocity magnitudes from 0.1 to 1.0 ms⁻¹ and surface observations from a research buoy in the Pacific that indicate the passage of gravity waves overhead as tropical cyclones pass by at distances of 100 to 300 km. Numerical simulations are used to interpret these observations and to understand the broader horizontal and vertical structures of the radiating waves. The simulations suggest a correlation between wave amplitude and cyclone intensity, which could be used to make remote estimates of peak wind speeds.

Wind profiles are essential for operational weather forecasting on all scales and at all latitudes. However, tropospheric winds are the number one unmet measurement objective for improving weather forecasts. In recent years, ground-based and airborne Doppler wind lidar (DWL) wind profiles have been used in field programs and various applications to obtain the necessary wind measurements. These measurements offer the opportunity to examine the impact of wind profiles on numerical weather prediction (NWP) . In addition, satellite-based DWL missions are also being planned. Observing System Simulation Experiments (OSSEs ) have been conducted to evaluate the impact of future space-based satellite global wind measurements on NWP. While many previous studies have emphasized global NWP systems, in this chapter we provide an overview and summary of recent studies with both data assimilation and OSSEs to demonstrate the value of DWL wind measurements in improving severe weather system forecasts in regional NWP, especially for systems with large societal impacts due to the damage they may cause (e.g., high-impact weather systems). Specifically, we give an overview of previous studies that have examined the impacts of ground-based and airborne DWL on the numerical predictions of mesoscale convective systems and hurricanes. The regional OSSE concept is introduced. Recent results with regional OSSEs using the mesoscale community Weather Research and Forecasting (WRF ) model and the NCEP Hurricane WRF (HWRF) model are presented. The potential configuration (e.g., resolution vs. accuracy) for future satellite-based DWL is evaluated. It is found that fairly good forecast impacts can be obtained from high-resolution observations with larger errors compared with accurate observations at a coarser resolution. Finally, the relative impact of ocean-surface wind measurements and 3-dimensional profiles is compared. The advantages of 3-D wind measurements are evident.

Hurricane Patricia was a historic tropical cyclone that broke many records, such as intensification rate, peak intensity, and overwater weakening rate, during its brief 4-day lifetime in late October 2015 in the eastern Pacific basin. Patricia confounded all of the intensity forecast guidance owing to its rapid intensity changes. Fortunately, the hurricane-penetrating National Oceanic and Atmospheric Administration WP-3D and U.S. Air Force C-130 aircraft and the National Aeronautics and Space Administration WB-57 high-altitude jet, under support of the Office of Naval Research, conducted missions through and over Patricia prior to and during its extreme intensity changes on all 4 days, while an extensive array of pressure sensors sampled Patricia after landfall. The observations collected from these missions include traditional data sources such as airborne Doppler radar and flight-level instruments as well as new data sources like a high-density array of dropsondes released from high-altitude and wide-swath radiometer. The combination of data from these sources and from satellites provides an excellent opportunity to investigate the physical processes responsible for Patricia’s structure and evolution and offers the potential to improve forecasts of tropical cyclone rapid intensity changes. This paper provides an overview of Patricia as well as the data collected during the aircraft missions.

The in situ generation of easterly waves (EWs) in the east Pacific (EPAC) is investigated using the Weather Research and Forecasting Model (WRF). The sensitivity of the model to the suppression of EW forcing by locally generated convective disturbances is examined. Specifically, local forcing of EWs is removed by reducing the terrain height in portions of Central and South America to suppress robust sources of diurnal convective variability, most notably in the Panama Bight. High terrain contributes to the initiation of mesoscale convective systems in the early morning that propagate westward into the EPAC warm pool. When such mesoscale convective systems are suppressed in the model, EW variance is significantly reduced. This result suggests that EPAC EWs can be generated locally in association with higher frequency convective disturbances, and these disturbances are determined to be an important source of EPAC EW variability. However, EPAC EW variability is not completely eliminated in such sensitivity experiments, indicating the importance for other sources of EW forcing, namely EWs propagating into the EPAC from west Africa. Examination of the EW vorticity budget in the model suggests that nascent waves are zonally elongated and amplified by horizontal advection and vertical stretching of vorticity. Changes in the mean state between the control run and simulation with reduced terrain height also complicate interpretation of the results.

We use a high resolution numerical simulation of Atlantic Hurricane Earl (2010) to increase our understanding of Earl's intensification in relatively strong vertical shear in the context of a recent paradigm for tropical cyclone intensification. The integrity of the simulation is judged by comparing analyses thereof with those of the unprecedented observational data gathered in Earl. Consistent with the classical view of spin up, the amplification of the tangential wind field above the boundary layer is found to occur as the absolute angular momentum surfaces are drawn inwards by the aggregate heating of the rotating convective clouds in the interior of the vortex. In addition to this classical pathway, spin up occurs within the inner-core boundary layer, where the maximum tangential winds occur. The latter is another element of the new paradigm. Despite the detrimental influence of the shear on the vortex alignment and on depressing the pseudo-equivalent potential temperature outside the developing eyewall, the combined eddy processes associated with the vortical plume structures in and around the developing eyewall region are shown to contribute to an enhanced overturning circulation and an intensifying storm. These eddy processes are distinctly agradient effects that are not features of the classical spin up mechanism. It remains to be understood how the rotating convective updraughts combine to produce the diagnosed structures of the eddy terms, themselves, and how vortex Rossby waves and other eddies contribute to the alignment of the vortex during intensification.

In order to determine how well a low-order wavenumber representation describes a hurricane wind speed field, given its natural variability in space and time, low-order wavenumber representations were calculated for hourly “snapshots” of the 10-m wind speed field generated by the current operational hurricane model. Two distinct periods were examined: the first when the storm is in a reasonably steady state over 7-8 hours; and the second where the storm is changing its internal structure over a similar time interval. Observing system sensitivity experiments were also performed using wind speed field time series obtained from interpolation of the model snapshots for each of the two periods. The time series were sampled along the flight legs of a typical “figure 4” aircraft flight pattern to simulate the surface wind data collection process to ascertain the effects of the wind speed field’s temporal and spatial variability upon the low-order wavenumber analyses. The comparison between the model wind speed field at any time and the wavenumber representations during the “steady-state” period shows that the essential features of the wind speed field are captured by wavenumber 0 and 1 and that including up to wavenumber 3 practically reproduces the model field. However, in the “non-steady” period the wavenumber 0 and 1 representation is frequently unable to capture the essential characteristics of the wind speed field. The observing system sensitivity experiments suggest that when the primary circulation is rapidly changing in amplitude and/or structure during the data collection period the low-order wavenumbers analysis of the wind speed field will only represent the temporal mean structure.

The Square-Root Ensemble Kalman Filter (ESRF) is a variant of the Ensemble Kalman Filter used with deterministic observations that includes a matrix square-root to account for the uncertainty of the unperturbed ensemble observations. Due to the difficulties in solving this equation, a serial approach is often used where observations are assimilated sequentially one after another. As previously demonstrated, in implementations to date the serial approach for the ESRF is suboptimal when used in conjunction with covariance localization as the Schur product used in the localization does not commute with assimilation. In this work we present a new algorithm for the direct solution of the ESRF equations based on finding the eigenvalues and eigenvectors of a sparse, square, symmetric positive semi-definite matrix with dimensions of the number of observations to be assimilated. This is amenable to direct computation using dedicated, massively parallel, and mature libraries. These libraries make it relatively simple to assemble and compute the observation principal components and solve the ESRF without using the serial approach. They also provide the eigenspectrum of the forward observation covariance matrix. Our parallel direct approach neglects the near-zero eigenvalues, which regularizes the problem. Numerical results show this approach is a highly scalable parallel method.

Idealized and real‐case simulations conducted using the Hurricane Weather Research and Forecasting (HWRF) model demonstrate a “top‐down” pathway to secondary eyewall formation (SEF) for tropical cyclones (TCs). For the real‐case simulations of Hurricane Rita (2005) and Hurricane Edouard (2014), a comparison to observations reveals the timing and overall characteristics of the simulated SEF appear realistic. An important control of the top‐down pathway to SEF is the amount and radial‐height distribution of hydrometeors at outer radii. Examination into the simulated hydrometeor particle fall speed distribution reveals that the HWRF operational microphysics scheme is not producing the lightest hydrometeors, which are likely present in observed TCs and are most conducive to being advected from the primary eyewall to the outer rainband region of the TC. Triggering of SEF begins with the fallout of hydrometeors at the outer radii from the TC primary eyewall, where penetrative downdrafts resulting from evaporative cooling of precipitation promote the development of local convection. As the convection‐induced radial convergence that is initially located in the midtroposphere extends downward into the boundary layer, it results in the eruption of high entropy air out of the boundary layer. This leads to the rapid development of rainband convection and subsequent SEF via a positive feedback among precipitation, convection, and boundary layer processes.

The paper uses observational data from 1950 to 2014 to investigate rapid intensification (RI) variability of tropical cyclones (TCs) in the North Atlantic and its relationships with large-scale climate variations. RI is defined as a TC intensity increase of at least 15.4 m/s (30 knots) in 24 h. The seasonal RI distribution follows the seasonal TC distribution, with the highest number in September. Although an RI event can occur anywhere over the tropical North Atlantic (TNA), there are three regions of maximum RI occurrence: (1) the western TNA of 12°N–18°N and 60°W–45°W, (2) the Gulf of Mexico and the western Caribbean Sea, and (3) the open ocean southeast and east of Florida. RI events also show a minimum value in the eastern Caribbean Sea north of South America—a place called a hurricane graveyard due to atmospheric divergence and subsidence. On longer time scales, RI displays both interannual and multidecadal variability, but RI does not show a long-term trend due to global warming. The top three climate indices showing high correlations with RI are the June-November ENSO and Atlantic warm pool indices, and the January-March North Atlantic oscillation index. It is found that variabilities of vertical wind shear and TC heat potential are important for TC RI in the hurricane main development region, whereas relative humidity at 500 hPa is the main factor responsible for TC RI in the eastern TNA. However, the large-scale oceanic and atmospheric variables analyzed in this study do not show an important role in TC RI in the Gulf of Mexico and the open ocean southeast and east of Florida. This suggests that other factors such as small-scale changes of oceanic and atmospheric variables or TC internal processes may be responsible for TC RI in these two regions. Additionally, the analyses indicate that large-scale atmospheric and oceanic variables are not critical to TC genesis and formation; however, once a tropical depression forms, large-scale climate variations play a role in TC intensification.

Satellite microwave sensors, both active scatterometers and passive radiometers, have been systematically measuring near-surface ocean winds for nearly 40 years, establishing an important legacy in studying and monitoring weather and climate variability. As an aid to such activities, the various wind datasets are being intercalibrated and merged into consistent climate data records (CDRs). The ocean wind CDRs (OW-CDRs) are evaluated by comparisons with ocean buoys and intercomparisons among the different satellite sensors and among the different data providers. Extending the OW-CDR into the future requires exploiting all available datasets, such as OSCAT-2 scheduled to launch in July 2016. Three planned methods of calibrating the OSCAT-2 σ_o measurements include: 1) direct Ku-band σ_o intercalibration to QuikSCAT and RapidScat; 2) multisensor wind speed intercalibration; and 3) calibration to stable rainforest targets. Unfortunately, RapidScat failed in August 2016 and cannot be used to directly calibrate OSCAT-2. A particular future continuity concern is the absence of scheduled new or continuation radiometer missions capable of measuring wind speed. Specialized model assimilations provide 30-year long high temporal/spatial resolution wind vector grids that composite the satellite wind information from OW-CDRs of multiple satellites viewing the Earth at different local times.

Offshore wind-energy development is planned for regions where hurricanes commonly occur, such as the USA Atlantic coast. Even the most robust wind-turbine design (IEC Class I) may be unable to withstand a Category-2 hurricane (hub-height wind speeds > 50 m⁻¹). Characteristics of the hurricane boundary layer that affect the structural integrity of turbines, especially in major hurricanes, are poorly understood, primarily due to a lack of adequate observations that span typical turbine heights (< 200 m above sea level). To provide these data, we use large-eddy simulations to produce wind profiles of an idealized Category-5 hurricane at high spatial (10 m) and temporal (0.1 s) resolution. By comparison with unique flight-level observations from a field project, we find that a relatively simple configuration of the Cloud Model I model accurately represents the properties of Hurricane Isabel (2003) in terms of mean wind speeds, wind-speed variances, and power spectra. Comparisons of power spectra and coherence curves derived from our hurricane simulations to those used in current turbine design standards suggest that adjustments to these standards may be needed to capture characteristics of turbulence seen within the simulated hurricane boundary layer. To enable improved design standards for wind turbines to withstand hurricanes, we suggest modifications to account for shifts in peak power to higher frequencies and greater spectral coherence at large separations.

Over the last decades, data from spaceborne synthetic aperture radar (SAR) have been used in hurricane research. However, some issues remain. When wind is at hurricane strength, the wind speed retrievals from single-polarization SAR may have errors because the backscatter signal may experience saturation and become double valued. By comparison, wind direction retrievals from cross-polarization SAR are not possible until now. In this paper, we develop a 2-D model, the symmetric hurricane estimates for wind (SHEW) model, and combine it with the modified inflow angle model to detect hurricane morphology and estimate the wind vector field imaged by cross-polarization SAR. By fitting SHEW to the SAR derived hurricane wind speed, we find the initial closest elliptical-symmetrical wind speed fields, hurricane center location, major and minor axes, the azimuthal (orientation) angle relative to the reference ellipse, and maximum wind speed. This set of hurricane morphology parameters, along with the speed of hurricane motion, are input to the inflow angle model, modified with an ellipse-shaped eye, to derive the hurricane wind direction. A total of 14 RADARSAT-2 ScanSAR images are employed to tune the combined model. Two SAR images acquired over Hurricane Arthur (2014) and Hurricane Earl (2010) are used to validate this model. Comparisons between the modeled surface wind vector and measurements from airborne stepped-frequency microwave radiometer and dropwindsondes show excellent agreement. The proposed method works well in areas with significant radar attenuation by precipitation.

This study presents multi-scale wind features observed in spaceborne synthetic aperture radar (SAR) images in tropical cyclones. Examples of eyewall mesovotices, spiral rainbands, fine-scale-band features, arc clouds, and boundary layer rolls are documented. Although these wind features are strongly tied to tropical cyclone dynamics and intensity based on previous numerical studies, they are not well-observed due to high rainfall and cloudiness that limits remote sensing instruments and the severe environment for in-situ observations to survive. Since SAR images view the actual ocean surface responses to storm-forced winds, they provide clear evidence for the presence of these wind features below clouds and their interaction with the sea surface. Analyses of the characteristics of boundary layer rolls based on SAR images show good agreement with in-situ aircraft observations, suggesting that a SAR image has a great potential to be utilized to study tropical cyclone low-level structure.

This study highlights infrared sensor technology incorporated into the Global Positioning System (GPS) dropsonde platforms to obtain sea surface temperature (SST) measurements. This modified sonde (IRsonde) is used to improve understanding of air-sea interaction in tropical cyclones (TCs). As part of the Sandy Supplemental project, IRsondes were constructed and then deployed during the 2014 hurricane season. Comparisons between SSTs measured by collocated IRsondes and ocean expendables show good agreement, especially in regions with no rain contamination. Surface fluxes were estimated using measurements from the IRsondes and AXBTs via a bulk method that requires measurements of SST and near-surface (10 m) wind speed, temperature and humidity. The evolution of surface fluxes and their role in the intensification and weakening of Hurricane Edouard (2014) are discussed in the context of boundary-layer recovery. Our result emphasizes the important role of surface-flux induced boundary-layer recovery in regulating the low-level thermodynamic structure that is tied to the asymmetry of convection and TC intensity change.

This study evaluates the impact of the modification of the vertical eddy diffusivity (K_m) in the boundary layer parameterization of the Hurricane Weather Research and Forecasting (HWRF) model on forecasts of tropical cyclone (TC) rapid intensification (RI). Composites of HWRF forecasts of Hurricanes Earl (2010) and Karl (2010) were compared for two versions of the planetary boundary layer (PBL) scheme in HWRF. The results show that using a smaller value of K_m, in better agreement with observations, improves RI forecasts. The composite-mean, inner-core structures for the two sets of runs at the time of RI onset are compared with observational, theoretical, and modeling studies of RI to determine why the runs with reduced K_m are more likely to undergo RI. It is found that the forecasts with reduced K_m at the RI onset have a shallower boundary layer with stronger inflow, more unstable near-surface air outside the eyewall, stronger and deeper updrafts in regions farther inward from the radius of maximum wind (RMW), and stronger boundary layer convergence closer to the storm center, although the mean storm intensity (as measured by the 10-m winds) is similar for the two groups. Finally, it is found that the departure of the maximum tangential wind from the gradient wind at the eyewall, and the inward advection of angular momentum outside the eyewall, is much larger in the forecasts with reduced K_m. This study emphasizes the important role of the boundary-layer structure and dynamics in TC intensity change, supporting recent studies emphasizing the boundary-layer spin-up mechanism, and recommends further improvement to the HWRF PBL physics.

The NASA Cyclone Global Navigation Satellite System (CYGNSS) is planned for launch in late 2016. It will make available frequent ocean surface wind speed observations throughout the life cycle of tropical storms and hurricanes. In this study, the impact of CYGNSS ocean surface winds on numerical simulations of a hurricane case is assessed with a research version of the Hurricane Weather Research and Forecasting model and a Gridpoint Statistical Interpolation data assimilation system in a regional observing system simulation experiment framework. Two different methods of reducing the CYGNSS data volume were tested; one in which the winds were thinned and one in which the winds were super-obbed. Results suggest that assimilation of the CYGNSS winds has great potential to improve hurricane track and intensity simulations through improved representations of the surface wind fields, hurricane inner-core structures, and surface fluxes. The assimilation of the super-obbed CYGNSS data seems to be more effective in improving hurricane track forecasts than thinning the data.

This study explores the behavior of the exchange coefficients for wind stress (C_D), sensible heat flux (C_H), and water vapor flux (C_E) as functions of surface wind speed (U₁₀) and atmospheric stability using direct turbulent flux measurements obtained from a platform equipped with fast-response turbulence sensors in a low-to-moderate wind region. Turbulent fluxes are calculated using the eddy-correlation method with extensive observations. The total numbers of quality-controlled 30 min flux runs are 12,240, 5813, and 5637 for estimation of C_D, C_H, and C_E, respectively. When adjusted to neutral stability using the Monin-Obukhov similarity theory (MOST), we found that C_DN, C_HN, and C_EN decrease with neutral-adjusted wind speed when wind speed is less than 5 m/s. C_DN is constant over the range 5 m/s < U_10N < 12 m/s, then increases with U_10N when U_10N > 12 m/s. In contrast, C_HN and C_EN exhibit no clear dependence on wind speed and are generally constant, with mean values of 0.96 × 10⁻³ and 1.2 × 10⁻³, respectively. This behavior of neutral exchange coefficients is consistent with the findings of previous studies. We also found that C_DN under offshore winds is generally greater than that under onshore wind conditions, which is ascribed to the younger wind waves present due to the shorter fetch in the former case. However, this behavior is not exhibited by C_HN or C_EN. The original C_D, C_H, and C_E values without MOST adjustment are also investigated to develop a new parameterization based on wind speed and stability. Three stability parameters are tested, including the bulk Richardson number, stability as defined in COARE 3.0, and a simplified Richardson number using the Charnock parameter. This new parameterization is free of MOST and the associated self-correlation. Compared with previous studies and COARE 3.0 results, the new parameterization using the simplified Richardson number performs well, with an increased correlation coefficient and reduction of root-mean-square error and bias.

A first observationally-based estimation of departures from gradient wind balance during secondary eyewall formation is presented. The study is based on the Atlantic Hurricane Edouard (2014). This storm was observed during the National Aeronautics and Space Administration’s (NASA) Hurricane and Severe Storm Sentinel (HS3) experiment, a field campaign conducted in collaboration with the National Oceanic and Atmospheric Administration (NOAA). A total of 135 dropsondes are analyzed in two separate time periods: one named the secondary eyewall formation period and the other one referred to as the decaying-double eyewalled storm period. During the secondary eyewall formation period, a time when the storm was observed to have only one eyewall, the diagnosed agradient force has a secondary maxima that coincides with the radial location of the secondary eyewall observed in the second period of study. The maximum spin up tendency of the radial influx of absolute vertical vorticity is within the boundary layer in the region of the eyewall of the storm and the spin up tendency structure elongates radially outward into the secondary region of supergradient wind, where the secondary wind maxima is observed in the second period of study. An analysis of the boundary-layer averaged vertical structure of equivalent potential temperature reveals a conditionally unstable environment in the secondary eyewall formation region. These findings support the hypothesis that deep convective activity in this region contributed to spin up of the boundary layer tangential winds and the formation of a secondary eyewall that is observed during the decaying-double eyewalled storm period.

The evolution of three successive hurricanes (Katia, Maria, and Ophelia) is investigated over the river plume area formed by the Amazon and Orinoco river outflows during September of 2011. The study focuses on hurricane impacts on the ocean structure and the ocean feedback influencing hurricane intensification. High-resolution (1/25° × 1/25° horizontal grid) numerical simulations of the circulation in the extended Atlantic Hurricane Region (Caribbean Sea, Gulf of Mexico, and Northwest Atlantic Ocean) were used to investigate the upper ocean response during the three hurricane-plume interaction cases. The three hurricanes revealed different evolution and intensification characteristics over an area covered by brackish surface waters. The upper ocean response to the hurricane passages over the plume affected region showed high variability due to the interaction of oceanic and atmospheric processes. The existence of a barrier layer (BL), formed by the offshore spreading of brackish waters, probably facilitated intensification of the first storm (Hurricane Katia) because the river-induced BL enhanced the resistance of the upper ocean to cooling. This effect was missing in the subsequent two hurricanes (Maria and Ophelia) as the eroded BL (due to Katia passage) allowed the upper ocean cooling to be increased. As a consequence, the amount of ocean thermal energy provided to these storms was greatly reduced, which acted to limit intensification. Numerical experiments and analyses, in tandem with observational support, lead to the conclusion that the presence of a river plume-induced BL is a strong factor in the ocean conditions influencing hurricane intensification.

One of the most important applications of a space-based Doppler Wind Lidar (DWL) would be to improve atmospheric analyses and weather forecasting. Since the mid-1980s, Observing System Simulation Experiments (OSSEs) have been conducted to evaluate the potential impact of space-based DWL data on numerical weather prediction (NWP). All of these OSSEs have shown significant beneficial impact on global analyses and forecasts. In more recent years, a limited number of OSSEs have been conducted to evaluate the potential impact of DWL data on hurricane forecasting and to also evaluate the impact of real airborne DWL observations. These latest studies suggest that DWL can complement existing hurricane observations effectively and should contribute to improved hurricane track and intensity forecasting.

A modular extensible framework for conducting Observing System Simulation Experiments (OSSEs) has been developed with the goals of (1) supporting decision-makers with quantitative assessments of proposed observing systems investments, (2) supporting readiness for new sensors, (3) enhancing collaboration across the community by making the most up-to-date OSSE components accessible, and (4) advancing the theory and practical application of OSSEs. This first implementation, the Community Global OSSE Package (CGOP), is for short- to medium-range global numerical weather prediction applications. The CGOP is based on a new mesoscale global nature run produced by NASA using the 7-km cubed sphere version of the Goddard Earth Observing System Model, version 5 (GEOS-5) Atmospheric General Circulation Model and the latest (January 2015) operational version of the NOAA global data assimilation (DA) system. CGOP includes procedures to simulate the full suite of observing systems used operationally in the global DA system, including conventional in situ, satellite-based radiance, and radio occultation observations. The methodology of adding a new proposed observation type is documented and illustrated with examples of current interest. The CGOP is designed to evolve, both to improve its realism and to keep pace with the advance of operational systems.

In 2011, the National Oceanic and Atmospheric Administration (NOAA) began a cooperative initiative with the academic community to address a vexing issue that has long been known as a disconnection between the operational and research realms for weather forecasting and data assimilation. The issue is the gap, or more exotically referred to as the "valley of death," between efforts within the broader research community and NOAA’s activities, which are heavily driven by operational constraints. With the stated goals of leveraging research community efforts to benefit NOAA’s mission and offering a path to operations for the latest research activities which support the NOAA mission, satellite data assimilation, in particular, this initiative aims to enhance the linkage between NOAA’s operational systems and the research efforts. A critical component is the establishment of an efficient Operations-To-Research (O2R) environment on the Supercomputer for Satellite Simulations and data assimilation Studies (S4). This O2R environment is critical for successful Research-To-Operations (R2O) transitions because it allows rigorous tracking, implementation, and merging of any changes necessary (to operational software codes, scripts, libraries, etc.) to achieve the scientific enhancement. So far, the S4 O2R environment, with close to 4700 computing cores (60 TFLOPs) and 1700 TB disk storage capacity, has been a great success and, consequently, was recently expanded to significantly increase its computing capacity. The objective of this article is to highlight some of the major achievements and benefits of this O2R approach, and some lessons learned, with the ultimate goal of inspiring other O2R/R2O initiatives in other areas and for other applications.

Horizontal wind, temperature, and moisture observations are presented from two Coyote Unmanned Aircraft System (UAS) flights in the boundary layer of Hurricane Edouard (2014). The first flight sampled the meteorological conditions in the eye and eyewall at altitudes from 900-1500 m while Edouard was a major hurricane (105 kt) on 16 September 2014. The following day, a second Coyote sampled the inflow layer outside of the storm core at ~760 m altitude, when Edouard had weakened to an 80-kt hurricane. These flights represent the first deployments of a UAS from an airborne manned aircraft into a tropical cyclone. Comparisons between the Coyote data and the Lockheed WP-3D Orion (WP-3D) flight-level measurements and analyses constructed from dropsonde data are also provided. On 16 September 2014, the Coyote-measured horizontal wind speeds agree, on average, to within ~1 m s^-1 of the wind speeds observed by the WP-3D, and reproduce the shape of the radial wind profile from the WP-3D measurements. For the inflow layer experiment on 17 September, the mean wind speeds from the Coyote and the dropsonde analysis differ by only 0.5 m s^-1, while the Coyote captured increased variability (σ = 3.4 m s^-1) in the horizontal wind field compared to the dropsonde analysis (σ = 2.2 m s^-1). Thermodynamic data from the Coyote and dropsondes agree well for both flights, with average discrepancies of 0.4°C and 0.0°C for temperature and 0.7°C and 1.3°C for dew point temperature on 16 and 17 September, respectively.

Numerical simulations, using the Weather Research and Forecasting (WRF) model in concert with GPS dropwindsondes released during the NASA African Monsoon Multidisciplinary Analyses 2006 Field Campaign, were conducted to provide additional insight on SAL-TC interaction. Using NCEP final analysis datasets to initialize the WRF, a sensitivity test was performed on the assimilated (i.e., observation nudging) GPS dropwindsondes to understand the effects of individual variables (i.e., moisture, temperature, and winds) on the simulation and determine the extent of improvement when compared to available observations. The results suggested that GPS dropwindsonde temperature data provided the most significant difference in the simulated storm organization, storm strength, and synoptic environment, but all of the variables assimilated at the same time give a more representative mesoscale and synoptic picture.

The evolution of rapidly intensifying Hurricane Karl (2010) is examined from a suite of remote sensing observations during the NASA Genesis and Rapid Intensification Processes (GRIP) field experiment. The novelties of this study are in the analysis of data from the airborne Doppler radar HIWRAP and the new Global Hawk airborne platform that allows long endurance sampling of hurricanes. Supporting data from the HAMSR microwave sounder coincident with HIWRAP and coordinated flights with the NOAA WP-3D aircraft help to provide a comprehensive understanding of the storm. The focus of the analysis is on documenting and understanding the structure, evolution, and role of small scale, deep convective forcing in the storm intensification process. Deep convective bursts are sporadically initiated in the downshear quadrants of the storm and rotate into the upshear quadrants for a period of ~12 h during the rapid intensification. The aircraft data analysis indicates that the bursts are being formed and maintained through a combination of two main processes: (1) convergence generated from counter-rotating mesovortex circulations and the larger vortex-scale flow; and (2) the turbulent (scales of ~25 km) transport of anomalously warm, buoyant air from the eye to the eyewall at low levels. The turbulent mixing across the eyewall interface and forced convective descent adjacent to the bursts assists in carving out the eye of Karl, which leads to an asymmetric enhancement of the warm core. The mesovortices play a key role in the evolution of the features described above. The Global Hawk aircraft allowed an examination of the vortex response and axisymmetrization period in addition to the burst pulsing phase. A pronounced axisymmetric development of the vortex is observed following the pulsing phase that includes a sloped eyewall structure and formation of a clear, wide eye.

As operational forecast and data assimilation (DA) systems evolve, observing system simulation experiment (OSSE) systems must evolve in parallel. Expected development of operational systems—especially the use of data that are currently not used or are just beginning to be used, such as all-sky and surface affected microwave radiances—will greatly challenge our ability to construct realistic OSSE systems. An additional set of challenges will arise when future DA systems strongly couple the different earth system components. In response, future OSSE systems will require coupled models to simulate nature and coupled observation simulators. The requirements for future evolving OSSE systems and potential solutions to satisfy these requirements are discussed. It is anticipated that in the future the OSSE technique will be applied to diverse and coupled domains with the use of increasingly advanced and sophisticated simulations of nature and observations.

This study provides a climatology (1981-2012) of landfalling tropical systems in the eastern U.S. Corn Belt and investigates the total contribution of these storms to the monthly climatological rainfall in the Midwestern United States. The primary focus is on rainfall impacts from landfalling tropical systems on historic corn yields at the climate division and crop reporting district level. Climatologically dry to drought conditions for historic monthly observed rainfall are identified using the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Index (SPI). It was found that without landfalling tropical system rainfall, the percentage increase in climatologically dry (or drier) conditions across the domain at state climate division resolution increased from 16% up to over 200%. The study also considers the effects of climatologically wet conditions on crop yields. Landfalling tropical system rainfall accounts for approximately 20% of the observed monthly rainfall during the tropical storm season (June-November) across the eastern U.S. Corn Belt (1981-2012). Correlation between the annual number of landfalling tropical systems and annual yield by state results in no relationship, but correlation of August monthly observed rainfall by climate division to crop reporting district annual yields has a weak-to-moderate, statistically-significant correlation in Ohio districts 30-60 and Indiana CRD 90. ANOVA analysis suggests that landfalling tropical rainfall may actually reduce yields in some states' climate divisions/crop reporting districts while increasing yield in others. Results suggest that there is a balance between landfalling tropical storms providing sufficient rainfall or too much rainfall to be of benefit to crops. Findings aim to provide information to producers, crop advisers, risk managers, and commodity groups so that seasonal hurricane forecasts can potentially be utilized in planning for above or below normal precipitation during phenologically important portions of the growing season.

A 12-year global database of rain-corrected satellite scatterometer surface winds for tropical cyclones (TCs) is used to produce composites of TC surface wind speed distributions relative to vertical wind shear and storm motion directions in each TC-prone basin and various TC intensity stages. These composites corroborate ideas presented in earlier studies, where maxima are located right of motion in the Earth-relative framework. The entire TC surface wind asymmetry is down motion left for all basins and for lower strength TCs after removing the motion vector. Relative to the shear direction, the motion-removed composites indicate that the surface wind asymmetry is located down shear left for the outer region of all TCs, but for the inner-core region it varies from left of shear to down shear right for different basin and TC intensity groups. Quantification of the surface wind asymmetric structure in further stratifications is a necessary next step for this scatterometer data set.

Satellite-based and high-altitude airborne remotely sensed air quality data complement land-based and routinely commercial-flight and other measurement-campaign acquired remotely sensed and in situ observations. It is important to optimize the combination and placement of these wide ranges of measurements and data acquisition options for cost-effectiveness. Under this initiative, we attempt to quantify the gain by a regional state-of-the-science chemical data assimilation and chemical transport modeling system when incremental sets of observation are acquired into the system. This study represents a first step in a series of steps to ingest such proposed incremental additions of observation. The efficacy of such proposals is quantified systematically by Observation Simulation System Experiments (OSSEs). We compared two end-to-end regional air quality forecasting simulations using: (a) the Weather Forecasting and Research (WRF) regional application initialized by the U.S. National Weather Service (NWS) Global Forecasting System (GFS) coupled with the U.S. Environmental Protection Agency Community Multi-scale Air Quality (CMAQ) chemical model (Byun and Schere, 2006), and (b) the same as above but with a new GFS enhanced by assimilating a fictitious addition of Atmospheric Infrared Sounder (AIRS) retrieved radiances at 13 km spatial resolution at nadir from a proposed geostationary satellite positioned over 75^oW staring over the U.S. Both sensitivity runs were performed in 12 km horizontal grid resolution and with daily initialization for 12 days between July 29 and August 9 2005. Noticeable forecast skill improvement in surface concentration for O₃ and particulate matter smaller than 2.5 µm in diameter (PM_2.5) was achieved.

We present a method to retrieve wind speeds in hurricanes from spaceborne passive microwave radiometer data. Brightness temperature T_B observations acquired at the 6.9-GHz horizontal polarization channel by the AMSR-E and AMSR2 onboard the Earth Observing System Aqua and Global Change Observation Mission-Water 1 satellites are selected for wind retrieval due to the fact that the signal at this frequency is sensitive to high wind speeds but less sensitive to rain scatter than those acquired at other higher frequency channels. The AMSR-E and AMSR2 observations of 53 hurricanes between 2002 and 2014 are collected and collocated with stepped-frequency microwave radiometer (SFMR) measurements. Based on the small slope approximation/small perturbation method model and an ocean surface roughness spectrum, the wind speeds are retrieved from the T_B data and validated against the SFMR measurements. The statistical comparison of the entire data set shows that the bias and root-mean-square error (RMSE) of the retrieved wind speeds are 1.11 and 4.34 m/s, respectively, which suggests that the proposed method can obtain high wind speeds under hurricane conditions. Two case studies show that the wind speed retrieval bias and RMSE are 1.08 and 3.93 m/s for Hurricane Earl and 0.09 and 3.23 m/s for Hurricane Edouard, respectively. The retrieved wind speeds from the AMSR-E and AMSR2 continuous three-day observations clearly show the process of hurricane intensification and weakening.

Advances in the study of tropical cyclones using aircraft observations came about through improvements (scientific and technological) in the ability to observe different aspects of the storms. Early studies provided the basis for understanding tropical cyclone structure and evolution (for an excellent overview see Dorst, 2007). Technological advances in aircraft in-situ and remote sensing observing capabilities, particularly the development of airborne Doppler radars, revolutionized our depiction of tropical cyclone structure and dynamics (for a review, see Marks, 2003).

The effects of surface flux parameterizations on tropical cyclone (TC) intensity and structure are investigated using the Advanced Research Weather Research and Forecasting (WRF-ARW) modeling system with high-resolution simulations of Typhoon Morakot (2009). Numerical experiments are designed to simulate Typhoon Morakot (2009) with different formulations of surface exchange coefficients for enthalpy (C_K) and momentum (C_D) transfers, including those from recent observational studies based on in situ aircraft data collected in Atlantic hurricanes. The results show that the simulated intensity and structure are sensitive to C_K and C_D, but the simulated track is not. Consistent with previous studies, the simulated storm intensity is found to be more sensitive to the ratio of C_K/C_D than to C_K or C_D alone. The pressure–wind relationship is also found to be influenced by the exchange coefficients, consistent with recent numerical studies. This paper emphasizes the importance of C_D and C_K on TC structure simulations. The results suggest that C_D and C_K have a large impact on surface wind and flux distributions, boundary layer heights, the warm core, and precipitation. Compared to available observations, the experiment with observed C_D and C_K generally simulated better intensity and structure than the other experiments, especially over the ocean. The reasons for the structural differences among the experiments with different C_D and C_K setups are discussed in the context of TC dynamics and thermodynamics.

This book deals primarily with monitoring, prediction, and understanding of tropical cyclones (TCs). It was envisioned to serve as a teaching and reference resource at universities and academic institutions for researchers and post-graduate students. It has been designed to provide a broad outlook on recent advances in observations, assimilation, and modeling of TCs with detailed and advanced information on genesis, intensification, movement, and storm-surge prediction. Specifically, it focuses on (i) state-of-the-art observations for advancing TC research, (ii) advances in numerical weather prediction for TCs, (iii) advanced assimilation and vortex initialization techniques, (iv) ocean coupling, (v) current capabilities to predict TCs, and (vi) advanced research in physical and dynamical processes in TCs. The chapters in the book are authored by leading international experts from academic, research, and operational environments. The book is also expected to stimulate critical thinking for cyclone forecasters and researchers, managers, policy makers, and graduate and post-graduate students to carry out future research in the field of TCs.

The structural evolution of the inner core and near-environment throughout the lifecycle of Hurricane Edouard (2014) is examined using a synthesis of airborne and satellite measurements. This study specifically focuses on differences in the distribution of deep convection during two periods: when Edouard intensified towards hurricane status and when Edouard peaked in intensity and began to weaken. While both periods saw precipitation maximized in the downshear left and upshear left quadrants, deep convection was only seen from the aircraft during the intensifying period. Deep convection was located farther inside the radius of maximum winds (RMW) during the intensifying period than the weakening period. This convection is traced to strong updrafts inside the RMW in the downshear right quadrant, tied to strong low-level convergence, and high convective available potential energy (CAPE) as the storm remained over warm water in a moist environment. Strong updrafts persisted upshear left and were collocated with high inertial stability in the inner core. During weakening, no deep convection was present, and the precipitation that was observed was associated with weaker convergence downshear right at larger radii, as CAPE was reduced from lower sea surface temperatures, reduced humidity from subsidence, and a stronger warm core. Weak updrafts were seen upshear left, with little coincidence with the high inertial stability of the inner core. These results highlight the importance of the azimuthal coverage of precipitation and the radial location of deep convection for intensification. A more symmetrical coverage can occur despite the presence of shear-driven azimuthal asymmetries in both the forcing and the local environment of the precipitation.

The Cyclone Global Navigation Satellite System (CYGNSS) is a new NASA Earth science mission scheduled to be launched in 2016 that focuses on tropical cyclones (TC) and tropical convection. The mission’s two primary objectives are the measurement of ocean surface wind speed with sufficient temporal resolution to resolve short time scale processes such as the rapid intensification phase of TC development, and the ability of its surface observations to penetrate through the extremely high precipitation rates typically encountered in the TC inner core. The mission’s goal is to support significant improvements in our ability to forecast TC track, intensity and storm surge through better observations and, ultimately, better understanding of inner core processes. CYGNSS meets its temporal sampling objective by deploying a constellation of eight satellites. Its ability to see through heavy precipitation is enabled by its operation as a bistatic radar using low frequency GPS signals. The mission will deploy an eight spacecraft constellation in a low inclination (35°) circular orbit to maximize coverage and sampling in the tropics. Each CYGNSS spacecraft carries a 4-channel radar receiver that measures GPS navigation signals scattered by the ocean surface. The mission will measure inner core surface winds with high temporal resolution and spatial coverage, under all precipitating conditions, and over the full dynamic range of TC wind speeds.

Previous studies have found surprisingly strong vertical motions in low levels of some tropical cyclones. In this study, all available dropsondes (~12,000) within tropical cyclones from 1997-2013 are examined, in order to create a dataset of the most extreme updrafts (≥ 10 m s⁻¹; 169 sondes) and wind speeds (≥ 90 m s⁻¹; 64 sondes). It is shown that extreme low-level (0-3 km) updrafts are ubiquitous within intense (Category 4 and 5) tropical cyclones, and that few such updrafts have been observed within weaker storms. These extreme updrafts, which are almost exclusively found within the eyewall just inwards of the radius of maximum winds, sometimes occur in close association with extreme horizontal wind speeds. Consistent with previous studies, it is suggested that both the extremes in vertical velocity and wind speed are associated with small-scale (~1 km) vortices that exist along the eye/eyewall interface. As a substantial number of updrafts are found within a kilometer of the surface, it can be shown that it is implausible for buoyancy to be the primary mechanism for vertical acceleration. Additionally, the azimuthal distribution of both the extreme updrafts and wind speeds is strongly associated with the orientation of the environmental vertical wind shear.

The structural evolution of the inner core and near-environment throughout the lifecycle of Hurricane Edouard (2014) is examined using a synthesis of airborne and satellite measurements. This study specifically focuses on the precipitation evolution and thermodynamic changes that occur on the vortex-scale during four periods: when Edouard was a slowly intensifying tropical storm, another while a rapidly intensifying hurricane, during the initial stages of weakening after reaching peak intensity, and later while experiencing moderate weakening in the midlatitudes. Results suggest that, in a shear-relative framework, a wavenumber-1 asymmetry exists whereby the downshear quadrants consistently exhibit the greatest precipitation coverage and highest relative humidity, while the upshear quadrants (particularly upshear right) exhibit relatively less precipitation coverage and lower humidity, particularly in the midtroposphere. Whether dynamically- or precipitation-driven, the relatively dry layers upshear appear to be ubiquitously caused by subsidence. The precipitation and thermodynamic asymmetry is observed throughout the intensification and later weakening stages, while a consistently more symmetric distribution is only observed when Edouard reaches peak intensity. The precipitation distribution, which is also discussed in the context of the boundary layer thermodynamic properties, is intimately linked to the thermodynamic symmetry, which becomes greater as the frequency, areal coverage, and, in particular, rainfall rate increases upshear. Although shear is generally believed to be detrimental to intensification, observations in Edouard also indicate that subsidence warming from mesoscale downdrafts in the low- to mid-troposphere very near the center may have contributed favorably to organization early in the intensification stage.

Effects caused by precipitation on the measurements of a three-dimensional sonic anemometer are analyzed based on a field observational experiment conducted in Maoming, Guangdong Province, China. Obvious fluctuations induced by precipitation are observed for the outputs of sonic anemometer-derived temperature and wind velocity components. A technique of turbulence spectra and cospectra normalized in the framework of similarity theory is utilized to validate the measured variables and calculated fluxes. It is found that the sensitivity of the sonic anemometer-derived temperature to precipitation is significant when compared with that of the wind velocity components. The spectra of wind velocity and cospectra of momentum flux resemble the standard universal shape, with the slopes of the spectra and cospectra at the inertial subrange following the −2/3 and −4/3 power law, respectively, even under the condition of heavy rain. Contaminated by precipitation, however, the spectra of temperature and cospectra of sensible heat flux do not exhibit a universal shape and have obvious frequency loss at the inertial subrange. From the physical structure and working principle of the sonic anemometer, a possible explanation is proposed to describe this difference, which is found to be related to the variations of precipitation particles. Corrections for errors of sonic anemometer-derived temperature under precipitation is needed, which is still under exploration.

In this study, the design of movable multi-level nesting (MMLN) in the Hurricane Weather Research and Forecasting (HWRF) modeling system is documented. The configuration of a new experimental HWRF system with a much larger horizontal outer domain and multiple sets of MMLN, referred to as the “basin-scale” HWRF, is also described. The performance of this new system is applied for various difficult forecast scenarios such as: (1) simulating multiple storms, i.e., Hurricanes Earl (2010), Danielle (2010), and Frank (2010); and (2) forecasting tropical cyclone (TC) to extratropical cyclone transitions, specifically Hurricane Sandy (2012). Verification of track forecasts for the 2011-2014 Atlantic and East Pacific hurricane seasons demonstrates that the basin-scale HWRF produces similar overall results to the 2014 operational HWRF, the best operational HWRF at the same resolution. In the Atlantic, intensity forecasts for the basin-scale HWRF were notably worse than for the 2014 operational HWRF, but this deficiency was shown to be from poor intensity forecasts for Hurricane Leslie (2012) associated with the lack of ocean coupling in the basin-scale HWRF. With Leslie removed, the intensity forecast errors were equivalent. The basin-scale HWRF is capable of predicting multiple TCs simultaneously, allowing more realistic storm-to-storm interactions. Even though the basin-scale HWRF produced results only comparable to the regular operational HWRF at this stage, this configuration paves a promising pathway toward operations.

NOAA has been gathering high-resolution flight-level, dropwindsonde and airborne Doppler radar data in tropical cyclones for almost three decades; the U.S. Air Force routinely obtained the same type and quality of data, excepting Doppler radar, for most of that time. The data have been used for operational diagnosis and for research, and, starting in 2013, have been assimilated into operational regional tropical cyclone models. This study is an effort to quantify the impact of assimilating these data into a version of the operational Hurricane Weather Research and Forecast model using an ensemble Kalman filter. Eighty-three cases from 2008-2011 were investigated. The aircraft whose data were used in the study all provide high-density flight-level wind and thermodynamic observations as well as surface wind speed data. Forecasts initialized with these data assimilated are compared to those using the model standard initialization. Since only NOAA aircraft provide airborne Doppler radar data, these data are also tested to see their impact above the standard aircraft data. The aircraft data alone are shown to provide some statistically significant improvement to track and intensity forecasts during the critical watch and warning period before projected landfall (through 60 h), with the Doppler radar data providing some further improvement. This study shows the potential for improved forecasts with regular tropical cyclone aircraft reconnaissance and the assimilation of data obtained from them, especially airborne Doppler radar data, into the numerical guidance.

Observing System Simulation Experiments (OSSEs) are an important tool for evaluating the potential impact of new or proposed observing systems, as well as for evaluating trade-offs in observing system design, and in developing and assessing improved methodology for assimilating new observations. Extensive OSSEs have been conducted at the National Aeronautical and Space Administration (NASA) Goddard Space Flight Center (GSFC) and the National Oceanic and Atmospheric Administration (NOAA) Atlantic Oceanographic and Meteorological Laboratory (AOML) over the last three decades. These OSSEs determined correctly the quantitative potential for several proposed satellite observing systems to improve weather analysis and prediction prior to their launch; evaluated trade-offs in orbits, coverage, and accuracy for space-based wind lidars; and were used in the development of the methodology that led to the first beneficial impacts of satellite surface winds on numerical weather prediction. This paper summarizes early applications of global OSSEs to hurricane track forecasting and new experiments using both global and regional models. These latter experiments are aimed at assessing potential impact on hurricane track and intensity prediction over the oceans and at landfall.

The potential impact of Doppler wind lidar (DWL) observations from a proposed optical autocovariance wind lidar (OAWL) instrument is quantified in observing system simulation experiments (OSSEs). The OAWL design would provide profiles of useful wind vectors along a ground track to the left of the International Space Station (ISS), which is in a 51.6° inclination low earth orbit (LEO). These observations are simulated realistically, accounting for cloud and aerosol distributions inferred from the OSSE nature runs (NRs), and measurement and sampling error sources. The impact of the simulated observations is determined in both global and regional OSSE frameworks. The global OSSE uses the ECMWF T511 NR and the NCEP operational global data assimilation (DA) system at T382 resolution. The regional OSSE uses an embedded hurricane NR and the NCEP operational HWRF DA system with outer and inner domains of 9 and 3 km resolution. The global OSSE results show improved analyses and forecasts of tropical winds and extratropical geopotential heights. The tropical wind RMSEs are significantly reduced in the analyses and in short term forecasts. The tropical wind improvement decays as the forecasts lengthen. The regional OSSEs are limited but show some improvements in hurricane track and intensity forecasts.

NOAA established the 10 year Hurricane Forecast Improvement Project (HFIP) to accelerate the improvement of forecasts and warnings of tropical cyclones and to enhance mitigation and preparedness by increased confidence in those forecasts. Specific goals include reducing track and intensity errors by 20% in 5 years and 50% in ten years and extending the useful range of hurricane forecasts to 7 days. Under HFIP, there have been significant improvements to NOAA’s operational hurricane prediction model resulting in increased accuracy in the numerical guidance for tropical cyclone intensity predictions. This paper documents many of the improvements that have been accomplished over the last 5 years, as well as some future research directions that are being pursued.

The Hurricane Weather Research and Forecasting (HWRF) model is an operational model used to provide numerical guidance in support of tropical cyclone forecasting at the National Hurricane Center. HWRF is a complex multi-component system, consisting of the Weather Research and Forecasting (WRF) atmospheric model coupled to the Princeton Ocean Model for Tropical Cyclones (POM-TC), a sophisticated initialization package including a data assimilation system, and a set of postprocessing and vortex tracking tools. HWRF's development is centralized at the Environmental Modeling Center of NOAA's National Weather Service, but it incorporates contributions from a variety of scientists spread out over several governmental laboratories and academic institutions. This distributed development scenario poses significant challenges: a large number of scientists need to learn how to use the model, operational and research codes need to stay synchronized to avoid divergence, and promising new capabilities need to be tested for operational consideration. This article describes how the Developmental Testbed Center has engaged in the HWRF developmental cycle in the last three years and the services it provides to the community in using and developing HWRF.

In this study, the results of a forecast from the operational Hurricane Weather Research and Forecasting (HWRF) system for Hurricane Earl (2010) are verified against observations and analyzed to understand the asymmetric rapid intensification of a storm in a sheared environment. The forecast verification shows that the HWRF model captured well Earl’s observed evolution of intensity, convection asymmetry, wind field asymmetry, and vortex tilt in terms of magnitude and direction in the pre-rapid and rapid intensification (RI) stages. Examination of the high-resolution forecast data reveals that the tilt was large at the RI onset and decreased quickly once RI commenced, suggesting that vertical alignment is the result instead of the trigger for RI. The RI onset is associated with the development of upper-level warming in the eye, which results from upper-level storm-relative flow advecting the warm air caused by subsidence warming in the upshear-left region towards the low-level storm center. This scenario does not occur until persistent convective bursts (CB) are concentrated in the downshear-left quadrant. The temperature budget calculation indicates that horizontal advection plays an important role in the development of upper-level warming in the early RI stage. The upper-level warming associated with the asymmetric intensification process occurs by means of the cooperative interaction of the convective-scale subsidence, resulting from CBs in favored regions and the shear-induced mesoscale subsidence. When CBs are concentrated in the downshear-left and upshear-left quadrants, the subsidence warming is maximized upshear and then advected towards the low-level storm center by the storm-relative flow at the upper level. Subsequently, the surface pressure falls and RI occurs.

Results from this multi-hurricane study suggest that the criticality of the oft-cited 26°C hurricane threshold linked to hurricane maintenance may be more closely associated with atmospheric thermodynamic conditions within the inner core than previously believed. In all cases, a positive sea-air contrast was observed within the storm inner core (i.e., surface ocean temperature greater than surface air temperature), despite the fact that 6% of the hurricanes exhibited sea surface temperatures (SST) less than the 26°C. For the storms sampled in this study, inner core surface dewpoint temperatures never exceeded 26.5°C. This finding may provide an alternate explanation as to the criticality of the 26°C threshold since SSTs above 26°C would, in almost all instances, be associated with a positive enthalpy flux condition. Analyses from this study also illustrate that high wind SSTs fluctuate as a function of storm latitude, while inner core near surface dewpoint temperatures are much less sensitive to this parameter. As a result, and assuming all other factors to be equal, low latitude hurricanes would, on average, be expected to experience surface moisture fluxes ~1/3 greater than storms located farther to the north. For systems sampled within the deep tropics, inner core SST was found to fluctuate much less than surface dewpoint temperature, suggesting that the atmosphere, not the ocean, is more likely to influence the key thermodynamic parameter controlling surface moisture flux for this subset of hurricanes.

The Hurricane Weather Research and Forecast system (HWRF) was operationally implemented with a 27-km outer domain and 9-km moving nest in 2007 (H007) as a tropical cyclone forecast model for the North Atlantic and Eastern Pacific hurricane basins. During the 2012 hurricane season, a modified version of the model (H212) that increased horizontal resolution by adding a third (3 km) nest within the 9-km nest replaced H007. H212 thus became the first operational model running at convection-permitting resolution. In addition, there were modifications to initialization, model physics, tracking algorithm, etc. This paper compares H212 model hindcast forecasts for the 2010-2011 Atlantic hurricane seasons with forecasts from H007 and H3GP, a triply-nested research HWRF version. H212 reduced track forecast errors for almost all forecast times versus H007 and H3GP. H3GP was superior for intensity forecasts, although H212 showed some improvement over H007. Stratifying the cases by initial vertical wind shear revealed that the main weakness for H212 intensity forecasts was for cases with initially high shear. In these cases, H212 over- and under-intensified storms that were initially stronger and weaker, respectively. These results suggest the primary deficiency negatively impacting H212 intensity forecasts, especially in cases of rapid intensification, was that physics calls were too infrequent for the 3-km inner mesh. Correcting this deficiency along with additional modifications in the 2013 operational version yielded improved track and intensity forecasts. These intensity forecasts were comparable to statistical/dynamical models, showing that dynamical models can contribute to a decrease in operational forecast errors.

Satellite microwave observations of rain, whether from radar or passive radiometers, depend in a very crucial way on the vertical distribution of the condensed water mass and on the types and sizes of the hydrometeors in the volume resolved by the instrument. This crucial dependence is nonlinear, with different types and orders of nonlinearity that are due to differences in the absorption/emission and scattering signatures at the different instrument frequencies. Because it is not monotone as a function of the underlying condensed water mass, the nonlinearity requires great care in its representation in the observation operator, as the inevitable uncertainties in the numerous precipitation variables are not directly convertible into an additive white uncertainty in the forward calculated observations. In particular, when attempting to assimilate such data into a cloud-permitting model, special care needs to be applied to describe and quantify the expected uncertainty in the observations operator in order not to turn the implicit white additive uncertainty on the input values into complicated biases in the calculated radiances. One approach would be to calculate the means and covariances of the nonlinearly calculated radiances given an a priori joint distribution for the input variables. This would be a very resource-intensive proposal if performed in real time. We propose a representation of the observation operator based on performing this moment calculation off line, with a dimensionality reduction step to allow for the effective calculation of the observation operator and the associated covariance in real time during the assimilation. The approach is applicable to other remotely sensed observations that depend nonlinearly on model variables, including wind vector fields. The approach has been successfully applied to the case of tropical cyclones, where the organization of the system helps in identifying the dimensionality-reducing variables.

Idealized coupled tropical cyclone (TC) simulations are conducted to isolate ocean impacts on intensity forecasts. A one-dimensional ocean model is embedded into the Hurricane Weather Research and Forecasting (HWRF) mesoscale atmospheric forecast model. By inserting an initial vortex into a horizontally uniform atmosphere above a horizontally uniform ocean, SST cooling rate becomes the dominant large-scale process controlling intensity evolution. Westward storm translation is introduced by bodily advecting ocean fields toward the east. The ocean model produces a realistic cold wake structure allowing the sensitivity of quasi-equilibrium intensity to storm (translation speed, size) and ocean (heat potential) parameters to be quantified. The atmosphere provides feedback through adjustments in 10-m temperature and humidity that reduce SST cooling impact on quasi-equilibrium intensity by up to 40%. When storms encounter an oceanic region with different heat potential, enthalpy flux adjustment is governed primarily by changes in air-sea temperature and humidity differences that respond within 2-4 h in the inner-core region, and secondarily by wind speed changes occurring over a time interval up to 18 h after the transition. Atmospheric feedback always acts to limit the change in enthalpy flux and intensity through adjustments in 10-m temperature and humidity. Intensity change is asymmetric, with a substantially smaller increase for storms encountering larger heat potential compared to the decrease for storms encountering smaller potential. The smaller increase results initially from the smaller wind speed present at the transition time plus stronger limiting atmospheric feedback. The smaller wind speed increase resulting from these two factors further enhances the asymmetry.

Recent studies have analyzed azimuthal mean slope of the tropical cyclone (TC) eyewall. This study looks at the shear-relative azimuthal variability of different metrics of eyewall slope: the 20 dBZ surface, the radius of maximum wind (RMW), and an angular momentum (M) surface passing through the RMW. The data used are Doppler radar composites from NOAA HRD. This study examines 34 TCs, with intensities ranging from 35-75 m/s and shear magnitudes ranging from 0-10 m/s. Calculation of the mean slope in each quadrant for all cases shows that RMW slope has the strongest asymmetry, with downshear slope larger than upshear in 62% of cases. Slopes of momentum surfaces and dBZ surfaces are also greater downshear in some cases (65% for M and 47% for dBZ), but there is more variance than in RMW slope. The azimuthal phase of maximum slope occurs most often downshear, particularly downshear left, consistent with the depiction of a mean vortex tilt approximately 10 degrees left of shear. Filtering the cases into high and low shear illustrates that the tendency for greater slope downshear is magnified for high-shear cases. In addition, although the dBZ slope shows less shear-relative signal overall, the difference between dBZ slope and momentum slope is an important factor in distinguishing between strengthening and weakening or steady TCs. Intensifying TCs tend to have dBZ surfaces that are more upright than M surfaces. Further investigation of these results will help to illustrate the ways in which vertical shear can play a role in altering the structure of the TC core region.

Using dropsondes from 27 aircraft flights, in-situ, and satellite data acquired during tropical cyclone Earl (category 4 hurricane), bulk air-sea fluxes of enthalpy and momentum are investigated in relation to intensity change and underlying upper-ocean thermal structure. During Earl’s rapid intensification (RI) period, ocean heat content (OHC) variability relative to the 26°C isotherm exceeded 90 kJ cm^-2, and sea surface cooling was less than 0.5°C. Enthalpy fluxes of ~1.1 kW m^-2 were estimated for Earl’s peak intensity. Daily sea surface heat losses of −6.5±0.8, −7.8±1.1, and +2.3±0.7 kJ cm^-2 were estimated for RI, mature, and weakening stages, respectively. A ratio C_K/C_D of the exchange coefficients of enthalpy (C_k) and momentum (C_D) between 0.54 and 0.7 produced reliable estimates for the fluxes relative to OHC changes, even during RI; a ratio C_K/C_D = 1 overestimated the fluxes. The most important result is that bulk enthalpy fluxes were controlled by the thermodynamic disequilibrium between the sea surface and the near-surface air, independently of wind speed. This disequilibrium was strongly influenced by underlying warm oceanic features; localized maxima in enthalpy fluxes developed over tight horizontal gradients of moisture disequilibrium over these eddy features. These regions of local buoyant forcing preferentially developed during RI. The overall magnitude of the moisture disequilibrium (Δq=q_s-q_a) was determined by the saturation specific humidity at sea surface temperature (q_s) rather than by the specific humidity of the atmospheric environment (q_a). These results support the hypothesis that intense local buoyant forcing by the ocean could be an important intensification mechanism in tropical cyclones over warm oceanic features.

New multi-lead time versions of three statistical probabilistic tropical cyclone rapid intensification (RI) prediction models are developed for the Atlantic and eastern North Pacific basins. These models are the linear-discriminant, analysis-based Statistical Hurricane Intensity Prediction Scheme Rapid Intensification Index (SHIPS-RII) and logistic regression and Bayesian statistical RI models. Consensus RI models derived by averaging the three individual RI model probability forecasts are also generated. A verification of the cross-validated forecasts of the above RI models conducted for the 12, 24, 36, and 48 h lead times indicates that these models generally exhibit skill relative to climatological forecasts with the eastern Pacific models, providing somewhat more skill than the Atlantic ones and the consensus versions providing more skill than the individual models. A verification of the deterministic RI model forecasts indicates that the operational intensity guidance exhibits some limited RI predictive skill, with the National Hurricane Center (NHC) official forecasts possessing the most skill within the first 24 h and the numerical models providing somewhat more skill at longer lead times. The Hurricane Weather Research and Forecasting (HWRF) model generally provides the most skillful RI forecasts of any of the conventional intensity models, while the new consensus RI model shows potential for providing increased skill over the existing operational intensity guidance. Finally, newly developed versions of the deterministic Rapid Intensification Aid guidance that employs the new probabilistic consensus RI model forecasts along with the existing operational intensity model consensus produces lower mean errors and biases than the intensity consensus model alone.

Synthetic aperture radar (SAR) images reveal the surface imprints of atmospheric occluded fronts. An occluded front is characterized as a low-wind zone located between and within two zones of higher winds blowing in the opposite directions on the left and right sides of the occluded front. A group of four SAR images reveal that the width of an individual occluded frontal zone and the wind magnitudes outside fronts vary greatly from case to case. In this paper, we performed a case study to analyze an occluded front observed by an Environmental Satellite (Envisat) Advanced SAR and ASCAT scatterometer along the west coast of Canada on November 24, 2011. The two-way interactive, triply nested grid (9-3-1 km) Weather Research and Forecasting (WRF) model was utilized to simulate the evolution of the occluded front. The occluded front moved toward the east during a 24-h model simulation, and the movement between 18:00 and 21:00 UTC matched the occluded front positions derived from the concurrently collected surface weather maps; from the National Oceanic and Atmospheric National Weather Service archives. The WRF-simulated low-wind zone associated with the occluded front and ocean surface wind speed match well with the SAR and scatterometer wind retrievals. High wind outside the front zone became weaker during the front evolution, whereas the width of the occluded frontal zone was contracted laterally. Analysis of the WRF model derived potential temperature field suggests that the occlusion process occurred below the 800-mb level. The structure of the occluded front studied here not only follows the conventional conceptual model and also supports the findings of a novel wrap-up conceptual model for an atmospheric frontal occlusion process.

The data from 438 Global Positioning System dropsondes in six typhoons are analyzed to investigate the mean atmospheric boundary layer structure in a composite framework. Following a recent study on boundary layer height in Atlantic hurricanes, we aim to quantify characteristics of boundary layer height scales in Western Pacific typhoons including the inflow layer depth (h_inflow), height of the maximum tangential wind speed (h_vtmax), and thermodynamic mixed layer depth. In addition, the kinematic and thermodynamic boundary layer structures are compared between the dropsonde composites using data in typhoons and hurricanes. Our results show that similar to the hurricane composite, there is a separation between the kinematic and thermodynamic boundary layer heights in typhoons, with the thermodynamic boundary layer depth being much smaller than h_inflow and h_vtmax in the typhoon boundary layer. All three boundary layer height scales tend to decrease toward the storm center. Our results confirm that the conceptual model of Zhang et al. (2011a) for boundary layer height variation is applicable to typhoon conditions. The kinematic boundary layer structure is generally similar between the typhoon and hurricane composites, but the typhoon composite shows a deeper inflow layer outside the eyewall than the hurricane composite. The thermodynamic structure of the typhoon boundary layer composite is warmer and moister outside the radius of maximum wind speed than the hurricane composite. This difference is attributed to different environmental conditions associated with typhoons compared to the hurricanes studied here.

The very severe cyclonic storm (VSCS) “Phailin (2013)” was the strongest cyclone that hit the eastern coast of India-Odisha state since the super cyclone of 1999. But the same story of casualties was not repeated as that of 1999 where approximately 10,000 fatalities were reported. In the case of Phailin, a record 1 million people were evacuated across 18,000 villages in both the Odisha and Andhra Pradesh states to coastal shelters following the improved operational forecast guidance, which benefited from highly skillful and accurate numerical model guidance for the movement, intensity, rainfall, and storm surge. Thus, the property damage and death toll were minimized through the proactive involvement of three tier disaster management agencies at central, state, and district levels.

The Hurricane Weather Research and Forecasting (HWRF) model is one of the premier models in NOAA’s operational suite of severe weather forecasting systems. An axiom in numerical weather prediction suggests that modeling the environment at high resolution optimizes forecast accuracy. However, due to operational time constraints, only the region immediately surrounding a single hurricane can be modeled in high resolution. Currently, this is achieved by embedding a relatively small high resolution, storm-following pair of grids within a larger and coarser grid. In a previous work, we extended HWRF to support multiple such independent storm-following pair of grids. The result was improved forecast accuracy by virtue of modeling storm-to-storm interactions in high resolution. However, some shortcomings in the underlying WRF framework cause these independent pairs of grids to be simulated sequentially. This limits the model’s scalability and makes  it impossible to harness this novel capability within the operational time constraints. In this paper, we address this issue by modifying the underlying WRF framework to simulate these independent pairs of storm-following grids in parallel. This is the first approach to be successfully implemented in the history of the WRF framework.

This work examines the applicability of a previously-postulated heuristic model for the temporal evolution of the small-amplitude tilt of a tropical cyclone-like vortex under vertical-shear forcing for both a dry and cloudy atmosphere. The heuristic model hinges on the existence of a quasi-discrete vortex-Rossby wave and its ability to represent the coherent precession and tilt-decay of a stable vortex in the free-alignment problem. Linearized numerical solutions for a dry and cloudy vortex confirm the model predictions that an increase in the magnitude of the radial potential vorticity (PV) gradient within the vortex skirt surrounding the core yields a more rapid evolution of a sheared vortex towards the equilibrium, left-of-shear tilt configuration. However, in the moist-neutral limit, in which the effective static stability vanishes in rising and sinking regions, the heuristic model yields a poor approximation to the simulated vortex core evolution, but a left-of-shear tilt of the near-core vortex, radially beyond the heating region, remains the preferred long-time solution. Within the near-core skirt the PV perturbation generated by vertical shearing exhibits continuous-spectrum type vortex-Rossby waves, features that are not captured by the heuristic model. Nevertheless, the heuristic model continues to predict the rapid vertical alignment and equilibrium, left-of-shear tilt configuration of the simulated near-core vortex in the moist-neutral limit.

The structure and evolution of Hurricane Earl (2010) during its rapid intensification as sampled by aircraft is studied here. Rapid intensification occurs in two stages. During the early stage, covering ~24 h, Earl was a tropical storm experiencing moderate northeasterly shear with an asymmetric distribution of convection, and the symmetric structure was shallow, broad, and diffuse. The upper-level circulation center was significantly displaced from the lower-level circulation at the beginning of this stage. Deep, vigorous convection, termed convective bursts, was located on the east side of the storm and appeared to play a role in positioning the upper-level cyclonic circulation center above the low-level center. By the end of this stage the vortex was aligned and extended over a deep layer, and rapid intensification began. During the late stage rapid intensification continued, as Earl intensified ~20 m s^-1 during the next 24 h. The vortex remained aligned in the presence of weaker vertical shear, though azimuthal asymmetries persisted that were characteristic of vortices in shear. Convective bursts concentrated near the radius of maximum winds, with the majority located inside the radius of maximum winds. Each of the two stages described here raises questions about the role of convective- and vortex-scale processes in rapid intensification. During the early stage the focus is on the role of convective bursts, and their associated mesoscale convective system, on vortex alignment and the onset of rapid intensification. During the late stage the focus is on the processes that explain the observed radial distribution of convective bursts which peak inside the radius of maximum winds.

The probabilistic prediction of tropical cyclone (TC) rapid intensification (RI) in the Atlantic and eastern Pacific Ocean basins is examined here using a series of logistic regression models trained on environmental and infrared satellite-derived features. The environmental predictors are based on averaged values over a 24-h period following the forecast time. These models are compared against equivalent models enhanced with additional TC predictors created from passive satellite microwave imagery (MI). Leave-one-year-out cross validation on the developmental dataset shows that the inclusion of MI-based predictors yields more skillful RI models for a variety of RI and intensity thresholds. Compared with the baseline forecast skill of the non-MI-based RI models, the relative skill improvements from including MI-based predictors range from 10.6–44.9%. Using archived real-time data in the period 2004-2013, evaluation of simulated real-time models is also carried out. Unlike in the model development stage, the simulated real-time setting involves using Global Forecast System forecasts for the non-satellite-based predictors instead of “perfect” observational-based predictors in the developmental data. In this case, the MI-based RI models still generate superior skill to the baseline RI models lacking MI-based predictors. The relative improvements gained in adding MI-based predictors are most notable in the Atlantic, where the non-MI versions of the models suffer acutely from the use of imperfect real-time data. In the Atlantic, relative skill improvements provided from the inclusion of MI-based predictors range from 53.5-103.0%. The eastern Pacific relative improvements are less impressive but are still uniformly positive.

In 1947, Robert H. Simpson lifted off in a specially equipped plane, flying directly into the path of a storm that would send most people running for cover. For more than four hours he observed Typhoon Martha from its eerily calm eye, later describing it in Scientific American as a coliseum of clouds whose walls on one side rose vertically and on the other were banked like the galleries in a great opera house. For Simpson this was just one of his many pioneering explorations of hurricanes and extreme storms. Over his decades-long career his research led to great leaps in our understanding of tropical meteorology and our approach to hurricane safety. He was the first director of the National Hurricane Research Project and a director of the National Hurricane Center, though he may be best known as co-creator of the widely used Saffir-Simpson Hurricane Scale, familiar to anyone who has heard a reporter use the words “category five.” Simpson's memoirs take readers from his experience with the Mississippi Flood of 1927 to his travels to study weather across the globe. Along the way he crosses paths with other weather greats, including his trailblazing wife, meteorologist Joanne Simpson. Hurricane Pioneer is a riveting first-hand account of a revolutionary time in meteorology.

An investigation into the possible causes of the rapid intensification (RI) of Hurricane Earl (2010) is carried out using a combination of global analyses, aircraft Doppler radar data, and observations from passive microwave satellites and a long-range lightning network. Results point to an important series of events leading to, and just after, the onset of RI, all of which occur despite moderate (7-12 m s^-1) vertical wind shear present. Beginning with an initially vertically misaligned vortex, observations indicate that asymmetric deep convection, initially left of shear but not distinctly up- or down-shear, rotates into more decisively upshear regions. Following this convective rotation, the vortex becomes aligned and precipitation symmetry increases. The potential contributions to intensification from each of these structural changes are discussed. The radial distribution of intense convection relative to the radius of maximum wind (RMW; determined from Doppler wind retrievals) is estimated from microwave and lightning data. Results indicate that intense convection is preferentially located within the upper-level (8-km) RMW during RI, lending further support to the notion that intense convection within the RMW promotes tropical cyclone intensification. The distribution relative to the low-level RMW is more ambiguous, with intense convection preferentially located just outside of the low-level RMW at times when the upper-level RMW is much greater than the low-level RMW.

Tropical cyclones (TC) consist of a large range of interacting scales from hundreds of kilometers to a few meters. The energy transportation amongst these different scales, i.e., from smaller to larger scales (upscale) or vice versa (downscale), may have profound impacts on TC energy dynamics due to the associated changes in available energy sources and sinks. From multi-layer tower measurements in the low-level (less than 120 m) boundary layer of several landing TCs, we found there are two distinct regions where the energy flux changes from upscale to downscale as a function of distance to the storm center. The boundary between these two regions is approximately 1.5 times the radius of maximum wind. Two-dimensional turbulence (upscale cascade) occurs more typically at regions close to the inner core region of TCs, while 3-D turbulence (downscale cascade) mostly occurs in the outer core region in the surface layer.

A GPS dropsonde is a scientific instrument deployed from research and operational aircraft that descends through the atmosphere by a parachute. The dropsonde provides high-quality, high vertical resolution profiles of atmospheric pressure, temperature, relative humidity, wind speed and direction from the aircraft flight level to the surface over oceans and remote areas. Since 1996, GPS dropsondes have been routinely dropped during hurricane reconnaissance and surveillance flights to help predict hurricane track and intensity. From 1996 to 2012, NOAA has dropped 13,681 dropsondes inside hurricane eye walls or in the surrounding environment for 120 tropical cyclones (TCs). All NOAA dropsonde data have been collected, reformatted to one format, and consistently and carefully quality-controlled using state-of-art quality-control (QC) tools. Three value-added products, the vertical air velocity and the radius and azimuth angle of each dropsonde location, are generated and added to the dataset. As a result, a long-term (1996–2012), high-quality, high-vertical resolution (∼5–15 m) GPS dropsonde dataset is created and made readily available for public access. The dropsonde data collected during hurricane reconnaissance and surveillance flights have improved TC track and intensity forecasts significantly. The milestones of dropsonde data's impact on hurricane studies are summarized. The scientific applications of this long-term dropsonde dataset are highlighted, including characterizing TC structures, studying TC environmental interactions, identifying surface-based ducts in hurricane environment which affect electromagnetic wave propagation, and validating satellite temperature and humidity profiling products.

A series of 5-day numerical simulations of idealized hurricane vortices under the influence of different background flows is performed by varying vertical grid resolution (VGR) in different portions of the atmosphere with the operational version of the Hurricane Weather Research and Forecasting model in order to study the sensitivity of hurricane intensity forecasts to different distributions of VGR. Increasing VGR from 21 to 43 levels produces stronger hurricanes, whereas increasing it further to 64 levels does not intensify the storms further, but with much reduced intensity fluctuations. Moreover, increasing the lower-level VGRs generates stronger storms, but the opposite is true for increased upper-level VGRs. On average, adding mean flow increases intensity fluctuations and variability (between the strongest and weakest hurricanes), whereas adding vertical wind shear (VWS) delays hurricane intensification and then causes more rapid growth in intensity variability. The stronger the VWS, the larger intensity variability and bifurcation rate occur at later stages. These intensity differences are found to be closely related to inner-core structural changes, and they are attributable to how much latent heat could be released in higher-VGR layers, followed by how much moisture content in nearby layers is converged. Hurricane intensity with higher VGRs is shown to be much less sensitive to varying background flows, and stronger hurricane vortices at the model initial time are less sensitive to the vertical distribution of VGR; the opposite is true for relatively uniform VGRs or weaker hurricane vortices. Results reveal that higher VGRs with a near-parabolic or Ω shape tends to produce smoother intensity variations and more typical inner-core structures.

This study examines the effects of horizontal diffusion on tropical cyclone (TC) intensity change and structure using idealized simulations of the Hurricane Weather and Research Forecast (HWRF) model. We conducted a series of sensitivity experiments with varying horizontal mixing lengths (L_h), but kept the vertical diffusion coefficient and other physical parameterizations unchanged. The results show that both simulated maximum intensity and intensity change are sensitive to the L_h used in the parameterization of the horizontal turbulent flux, in particular, for L_h less than the model’s horizontal resolution. The results also show that simulated storm structures such as storm size, kinematic boundary layer height, and eyewall slope are sensitive to L_h as well. However, L_h has little impact on the magnitude of the surface inflow angle and thermodynamic mixed layer height. Angular momentum budget analyses indicate that the effect of L_h is to mainly spin down a TC vortex. Both mean and eddy advection terms in the angular momentum budget are affected by the magnitude of L_h. For smaller L_h, the convergence of angular momentum is larger in the boundary layer, which leads to a faster spin-up of the vortex. The resolved-eddy advection of angular momentum plays an important role in the spin-up of the low-level vortex inward from the radius of the maximum wind speed when L_h is small.

As part of the Hurricane Forecast Improvement Project (HFIP), recent boundary-layer physics upgrades in the operational Hurricane Weather Research and Forecasting (HWRF) model have benefited from analyses of in-situ aircraft observations in the low-level eyewall region of major hurricanes. This study evaluates the impact of these improvements to the vertical diffusion in the boundary layer on the simulated track, intensity, and structure of four hurricanes using retrospective HWRF forecasts. Structural metrics developed from observational composites are used in the model evaluation process. The results show improvements in track and intensity forecasts in response to the improvement of the vertical diffusion. The results also demonstrate substantial improvements in the simulated storm size, surface inflow angle, near-surface wind profile and kinematic boundary layer heights in simulations with the improved physics, while only minor improvements are found in the thermodynamic boundary layer height, eyewall slope, and the distributions of vertical velocities in the eyewall. Other structural metrics such as warm core anomaly and warm core height are also explored. Reasons for the structural differences between the two sets of forecasts with different physics are discussed. This work further emphasizes the importance of aircraft observations in model diagnostics and development, endorsing a developmental framework for improving physical parameterizations in hurricane models.

Two idealized simulations by the Hurricane Weather Research and Forecast (HWRF) model are presented to examine the impact of model physics on the simulated eyewall replacement cycle (ERC). While no ERC is produced in the control simulation that uses the operational HWRF physics, the sensitivity experiment with different model physics generates an ERC that possesses key features of observed ERCs in real tropical cyclones. Likely reasons for the control simulation not producing ERC include lack of outer rainband convection at the far radii from the eyewall, excessive ice hydrometeors in the eyewall, and enhanced moat shallow convection, which all tend to prevent the formation of a persistent moat between the eyewall and outer rainband. Less evaporative cooling from precipitation in the outer rainband region in the control simulation produces a more stable and dryer environment that inhibits the development of systematic convection at the far radii from the eyewall.

A simple linear discriminant analysis scheme using climatological predictors is derived for the Atlantic basin as a no-skill baseline for operational phase forecasts from the National Hurricane Center. The model with independent data correctly classifies 80% of the cases at 12 h, and this value decreases to about 45% by 60 h, remaining steady thereafter. Using the same cases, NHC-issued phase predictions were more frequency accurate than the baseline, so their forecasts are said to have skill.

Observing System Simulation Experiments (OSSEs) are an important tool for evaluating the potential impact of proposed new observing systems, as well as for evaluating trade-offs in observing system design, and in developing and assessing improved methodology for assimilating new observations. Extensive OSSEs have been conducted at NASA/ GSFC and NOAA/AOML over the last three decades. These OSSEs determined correctly the quantitative potential for several proposed satellite observing systems to improve weather analysis and prediction prior to their launch, evaluated trade-offs in orbits, coverage and accuracy for space-based wind lidars, and were used in the development of the methodology that led to the first beneficial impacts of satellite surface winds on numerical weather prediction. In this paper, we summarize early applications of global OSSEs to hurricane track forecasting and new experiments using both global and regional models. These experiments are aimed at determining (1) the potential impact of unmanned aerial systems, (2) the relative impact of alternative concepts for space-based lidar winds, and (3) the relative impact of alternative concepts for polar and geostationary hyperspectral sounders.

The three-dimensional global wind field is the most important remaining measurement needed to accurately assess the dynamics of the atmosphere. Wind information in the tropics, high latitudes, and stratosphere, is particularly deficient. Furthermore, only a small fraction of the atmosphere is sampled in terms of wind profiles. This limits our ability to optimally specify initial conditions for numerical weather prediction (NWP) models and our understanding of several key climate change issues. Because of its extensive wind-measurement heritage (since 1968) and especially the rapid recent technology advances, Doppler lidar has reached a level of maturity required for a space-based mission. ESA’s Atmospheric Dynamics Mission (ADM)-Aeolus Doppler Wind Lidar (DWL), now scheduled for launch in 2015, will be a major milestone. This paper reviews the expected impact of DWL measurements on NWP and climate research, measurement concepts, and the recent advances in technology that will set the stage for space-based deployment. Forecast impact experiments with actual airborne DWL measurements collected over the North Atlantic in 2003 and assimilated into the European Centre for Medium-Range Weather Forecasts (ECMWF) operational model are a clear indication of the value of lidar-measured wind profiles. Airborne DWL measurements collected over the Western Pacific in 2008 and assimilated into both the ECMWF and U.S. Navy operational models support the earlier findings. These forecast impact experiments confirm Observing System Simulation Experiments (OSSEs) conducted over the past 25-30 years. The addition of simulated DWL wind observations in recent OSSEs performed at the Joint Center for Satellite Data Assimilation (JCSDA) leads to a statistically significant increase in forecast skill.

Airborne Doppler radar data collected in tropical cyclones by National Oceanic and Atmospheric Administration WP-3D aircraft over an eight-year period (2003-2010) is used to statistically analyze the vertical structure of tropical cyclone eyewalls with reference to the deep layer shear. Convective evolution within the inner core conforms to patterns shown by previous studies: convection initiates downshear-right, intensifies downshear-left and weakens upshear. Analysis of the vertical distribution of radar reflectivity and vertical air motion indicates the development of upper-level downdrafts in conjunction with strong convection downshear-left and a maximum in frequency upshear-left. Intense updrafts and downdrafts both conform to the shear asymmetry pattern. While strong updrafts occur within the eyewall, intense downdrafts show far more radial variability, particularly in the upshear-left quadrant, though they concentrate along the eyewall edges. Strong updrafts are collocated with low-level inflow and upper-level outflow superimposed on the background flow. In contrast, strong downdrafts occur in association with low-level outflow and upper-level inflow.

The diurnal cycle of tropical convection and the tropical cyclone (TC) cirrus canopy have been described extensively in previous studies. However, a complete understanding of the TC diurnal cycle remains elusive and is an area of ongoing research. This work describes a new technique that uses infrared satellite image differencing to examine the evolution of the TC diurnal cycle for all North Atlantic major hurricanes from 2001-2010. The imagery reveals cyclical pulses in the infrared cloud field that regularly propagate radially outward from the storm. These diurnal pulses begin forming in the storm’s inner core near the time of sunset each day and continue to move away from the storm overnight, reaching areas several hundred kilometers from the circulation center by the following afternoon. A marked warming of the cloud tops occurs behind this propagating feature and there can be pronounced structural changes to a storm as it moves away from the inner core. This suggests that the TC diurnal cycle may be an important element of TC dynamics and may have relevance to TC structure and intensity change. Evidence is also presented showing the existence of statistically significant diurnal signals in TC wind radii and objective Dvorak satellite-based intensity estimates for the 10-yr hurricane dataset that was examined. Findings indicate that TC diurnal pulses are a distinguishing characteristic of the TC diurnal cycle and the repeatability of TC diurnal pulsing in time and space suggests that it may be an unrealized, yet fundamental TC process.

This report describes the activities and results of the Hurricane Forecast Improvement Program (HFIP) in 2013. Since this is the fourth year of the first five years of the project, we, like last year, focus on the improvements in the operational Global Forecast System (GFS) global model and the Hurricane Weather Research and Forecasting (HWRF) regional model. HFIP is organized around the three “streams”: Stream 1 or the operational model development; Stream 1.5 which comprises a group of experimental models that have been evaluated by the National Hurricane Center (NHC) pre-season and then made available to NHC forecasters during their forecast cycle; and Stream 2 representing HFIP experimental models which test and evaluate new techniques and strategies for model forecast guidance before testing is begun for possible operational implementation. Stream 2 also tests techniques that cannot be tested on current operational computers because of their size and time requirements, but can be tested on HFIP computer facilities in Boulder, Colorado. Those studies are looking ahead to possible future operational computational capability. The report outlines the HFIP program, how it is organized, its goals, its models, and then results from each of the three streams.

A new fraternal twin ocean Observing System Simulation Experiment (OSSE) system is validated in a Gulf of Mexico domain. It is the first ocean system that takes full advantage of design criteria and rigorous evaluation procedures developed to validate atmosphere OSSE systems that have not been fully implemented for the ocean. These procedures are necessary to determine a-priori that the OSSE system does not overestimate or underestimate observing system impacts. The new system consists of (1) a nature run (NR) stipulated to represent the true ocean; (2) a data assimilation system consisting of a second ocean model (the “forecast model”) coupled to a new ocean data assimilation system; and (3) software to simulate observations from the NR and add realistic errors. System design is described to illustrate the requirements of a validated OSSE system. The chosen NR reproduces the climatology and variability of ocean phenomena with sufficient realism. Although the same ocean model type is used (the “fraternal twin” approach), the forecast model is configured differently so that it satisfies the requirement that differences (errors) with respect to the NR grow at the same rate as errors that develop between state-of-the-art ocean models and the true ocean. Rigorous evaluation procedures developed for atmospheric OSSEs are then applied by first performing Observing System Experiments (OSEs) to evaluate one or more existing observing systems. OSSEs are then performed that are identical except for the assimilation of synthetic observations simulated from the NR. Very similar impact assessments were realized between each OSE-OSSE pair, thus validating the system without the need for calibration.

Progress in understanding the formation of ice in lower tropospheric clouds is slowed by the difficulties in characterizing the many complex interactions that lead to ice initiation and to the dynamic, non-steady state nature of the clouds. The present study characterizes the conditions where secondary ice particles, specifically identified as needle or thin columnar types, are observed in tropical maritime convection with modest liquid water contents during the Ice in Clouds Experiment-Tropical (ICE-T), based out of St. Croix, V. I., and the NASA African Monsoon Multidisciplinary Analysis experiment (NAMMA) in 2006 sampling from Cape Verde, Africa. The properties of the cloud droplet populations relevant to the secondary ice production process, and the ice particle populations, are characterized as a function of temperature and vertical velocity. These secondary ice particles are observed primarily in regions of low liquid water content and weak vertical velocities. Two situations are examined in detail. First, ice formation is examined by following the tops of a group of ICE-T chimney clouds as they ascend and cool from a temperature of +7°C to −8°C, examining the production of the first ice. Then, using the data from a cloud system sampled during NAMMA, we elucidate a process that promotes ice multiplication. The intention is that this study will lead both to a better understanding of how secondary ice production proceeds in natural clouds as well as to more realistic laboratory studies of the processes involved.

Surface wind speeds retrieved from airborne stepped frequency microwave radiometer (SFMR) brightness temperature measurements are important for estimating hurricane intensity. The SFMR performance is highly reliable at hurricane force wind speeds, but accuracy is found to degrade at weaker wind speeds, particularly in heavy precipitation. Specifically, a significant over-estimation of surface wind speeds is found in these conditions, suggesting inaccurate accounting for the impact of rain on the measured microwave brightness temperature. In this study, the wind speed bias is quantified over a broad range of operationally-computed wind speeds and rain rates, based on a large sample of co-located SFMR wind retrievals and Global Positioning System dropwindsonde surface-adjusted wind speeds. The retrieval bias is addressed by developing a new SFMR C-band microwave absorption—rain rate (κ-R) relationship from National Oceanic and Atmospheric Administration WP-3D aircraft tail Doppler radar reflectivity and in situ Droplet Measurement Technologies Precipitation Imaging Probe measurements to more accurately model precipitation impacts. Absorption is found to be a factor of two weaker than is estimated by the currently-operational algorithm. With this new κ-R relationship, surface wind retrieval bias is significantly reduced in the presence of rain at wind speeds weaker than hurricane force. At wind speeds greater than hurricane force where little bias exists, no significant change is found. Furthermore, maximum rain rates computed using the revised algorithm are around 50% greater than operational measurements, which is more consistent with maximum reflectivity-estimated rain rates in hurricanes.

As part of NOAA’s Hurricane Forecast Improvement Program (HFIP), this paper addresses the important role of aircraft observations in hurricane model physics validation and improvement. A model developmental framework for improving the physical parameterizations using quality-controlled and post-processed aircraft observations is presented, with steps that include model diagnostics, physics development, physics implementation and further evaluation. Model deficiencies are first identified through model diagnostics by comparing the simulated axisymmetric multi-scale structures to observational composites. New physical parameterizations are developed in parallel based on in-situ observational data from specially designed hurricane field programs. The new physics package is then implemented in the model, which is followed by further evaluation. The developmental framework presented here is found to be successful in improving the surface layer and boundary layer parameterization schemes in the operational Hurricane Weather Research and Forecast (HWRF) model. Observations for improving physics packages other than boundary layer scheme are also discussed.

This paper analyzes data collected from a new set of observational platforms in the coastal area of China, which consist of a mobile observation system, meteorological tower, automatic weather station, and Doppler radars, to investigate the mean and turbulent boundary layer structure and evolution during the landfall of typhoons. An example of these data is provided from Typhoon Morakot (2009). Vertical profiles of wind velocities and thermodynamic parameters from the observed data allow us to identify different boundary layer structures during and after landfall. These structures, sampled in regions of the outer core, are stratified into periods where convection is occurring (termed “convective”) and periods where convection has recently (‹2 h) occurred (termed “postconvective”). Data analyses show that the thermodynamic mixed-layer depth and inflow layer depth are higher during the convective period than the postconvective period. The mixed-layer depth is found to be within the strong inflow layer, but the height of the maximum tangential wind speed is above the inflow layer during both periods, contrary to recent observational studies of the boundary-layer structure of tropical cyclones over water. High-frequency wind data show that momentum flux, turbulent kinetic energy (TKE), and integral length scales of wind velocities are all much larger during the convective period than the postconvective period. The results suggest that convective downdrafts may play an important role in modulating turbulent flux, TKE, vertical mixing, and boundary layer recovery processes.

We examine dynamic and thermodynamic aspects of Atlantic Hurricane Earl (2010) during its intensification and mature phases over four days of intensive measurements. During this period, Earl underwent an episode of rapid intensification, maturity, secondary eyewall replacement, re-intensification, and the early part of the decline. The observations are used to appraise elements of a new model for tropical-cyclone intensification. The results affirm the conventional (vortex interior) and boundary layer spin up mechanisms that form dynamical elements of the azimuthally-averaged view of the new intensification model. The average maximum tangential winds beneath the eyewall are found to exceed the gradient wind by between 20% and 60%. The results suggest also that the gradient wind balance approximation in the low-level vortex interior above the boundary layer may not be as accurate as has been widely held in the inner-core region of a tropical cyclone during its intensification. An analysis of the low-level thermodynamic structure affirms the radial increase of moist equivalent potential temperature, θ_e, with decreasing radius during the intensification process, a necessary ingredient of the new model for maintaining convective instability in the presence of a warming upper-troposphere. An unanticipated finding is the discovery of an unmixed boundary layer in terms of θ_e over several hundred kilometers of the vortex. In the inner-core region, this finding is not consistent with the axisymmetric eruption of the boundary layer into the eyewall unless there are non-conservative (eddy) processes acting to modify the entropy of ascending air.

Topography affects the patterns of forest disturbance produced by tropical cyclones. It determines the degree of exposure of a surface and can alter wind characteristics. Whether multispectral remote sensing data can sense the effect of topography on disturbance is a question that deserves attention given the multi-scale spatial coverage of these data and the projected increase in intensity of the strongest cyclones. Here, multispectral satellite data, topographic maps, and cyclone surface wind data were used to study the patterns of disturbance in an Australian rainforest with complex mountainous terrain produced by tropical cyclone Yasi (2011). The cyclone surface wind data (H*wind) was produced by the Hurricane Research Division of the National Oceanic and Atmospheric Administration (HRD/NOAA), and this was the first time that this data was produced for a cyclone outside of United States territory. A disturbance map was obtained by applying spectral mixture analyses on satellite data and presented a significant correlation with field-measured tree mortality. Our results showed that, consistent with cyclones in the southern hemisphere, multispectral data revealed that forest disturbance was higher on the left side of the cyclone track. The highest level of forest disturbance occurred in forests along the path of the cyclone track (±30°). Levels of forest disturbance decreased with decreasing slope and with an aspect facing off the track of the cyclone or away from the dominant surface winds. An increase in disturbance with surface elevation was also observed. However, areas affected by the same wind intensity presented increased levels of disturbance with increasing elevation, suggesting that complex terrain interactions act to speed up wind at higher elevations. Yasi produced an important offset to Australia’s forest carbon sink in 2010. We concluded that multispectral data were sensitive to the main effects of complex topography on disturbance patterns. High resolution cyclone wind surface data are needed in order to quantify the effects of topographic accelerations on cyclone related forest disturbances.

This study uses an observing system simulation experiment (OSSE) approach to test the limitations of even nearly ideal observing systems to capture the peak wind speed occurring within a tropical storm or hurricane. The data set is provided by a 1-km resolution simulation of an Atlantic hurricane with surface wind speeds saved every 10 seconds. An optimal observing system consisting of a dense field of anemometers provides perfect measurements of the peak 1-minute wind speed as well as the average peak wind speed. Suboptimal observing systems consisting of a small number of anemometers are sampled and compared to the truth provided by the optimal observing system. Results show that a single, perfect anemometer experiencing a direct hit by the right side of the eyewall will underestimate the actual peak intensity by 10-20%. Even an unusually large number of anemometers (e.g., 3-5) experiencing direct hits by the storm together will underestimate the peak wind speeds by 5-10%. However, the peak winds of just one or two anemometers will provide on average a good estimate of the average peak intensity over several hours. Enhancing the variability of the simulated winds to better match observed winds does not change the results. Adding observational errors generally increases the reported peak winds, thus reducing the underestimates. If the average underestimate (negative bias) were known perfectly for each case, it could be used to correct the wind speeds, leaving only mean absolute errors of 3-5%.

A tropical cyclone is one of the most hazardous weather events over the data sparse warm tropical ocean. It is the most deadly weather system and causes destructive winds, heavy rainfall, high storm surges, and coastal inundation, usually resulting in serious property damage and loss of life in coastal belts of India and, hence, strong impact on the socio-economic conditions of the countries surrounding the Bay of Bengal, especially India, Bangladesh, and Myanmar. The Bay of Bengal contributes about 5% of the global annual total number of tropical storms (Mohanty, 1994). Moreover, the Bay of Bengal storms are exceptionally devastating, especially when they cross the land (De Angelis, 1976). Therefore, the Bay of Bengal tropical cyclone disaster is the costliest and deadliest natural hazard on the Indian subcontinent.

Quantifying and reducing the uncertainty of model parameterizations using observations is evaluated for tropical cyclone (TC) intensity prediction. This is accomplished using a nonlinear inverse modeling technique that produces a joint probability density function (PDF) for a set of parameters. The dependence of estimated parameter values and associated uncertainty on two types of observable quantities is analyzed using an axisymmetric hurricane model. When the observation is only the maximum tangential wind speed, the joint PDF of parameter estimates has large variance and is multimodal. When the full kinematic field within the inner core of the TC is used for the observations, however, the joint parameter estimates are well constrained. These results suggest that model parameterizations may not be optimized using the maximum wind speed. Instead, the optimization should be based on observations of the TC structure to improve the intensity forecasts.

This paper completes a series of studies using a 2-D hybrid Lagrangian-Eulerian model to investigate the effect of sea spray on the thermodynamics and microphysics of the hurricane mixed layer. The evolution of the mixed layer was simulated by mimicking the motion of an air-volume (in a Lagrangian sense) toward a tropical cyclone eyewall along a background air-flow. During the radial motion, sea surface temperature, as well as pressure, background wind speed, sea spray production rate and turbulence intensity were altered according to the available observations. Analysis of the interaction between the hurricane mixed layer and the upper layers in terms of entrainment heat and moisture fluxes gives a new insight into the role of sea spray in the thermodynamics and microphysics of the mixed layer. The evaporation of sea spray leads to an increase in the relative humidity by 10-15% and to a decrease in temperature by ~1-1.5 K, as compared to cases where sea spray is excluded. Sea spray leads to formation of drizzling clouds with the cloud base at the height of about 250 m. Taking sea spray effect into account provides a good agreement between the thermodynamics of a simulated mixed layer and the observation data. A parameterization of droplet mass and size distributions as functions of height and wind speed is proposed. The horizontally averaged size distributions are approximated by a sum of lognormal distributions. The moments of size distributions and other integral properties are parameterized as functions of 10-m wind speed by means of simple polynomial expressions.

The recent study of the sensitivity of tropical-cyclone intensification to the surface drag coefficient in a three-dimensional model by Montgomery et al. is extended to include a wind-speed-dependent drag coefficient and one of four boundary-layer parametrization schemes: the bulk, Blackadar, MRF, and Gayno-Seaman schemes. The schemes are slightly modified to have the same drag coefficient formulation and the same constant exchange coefficients for sensible heat and moisture. Interest is focused on the change in intensity of the azimuthally-averaged tangential wind speed and change in the low-level vortex structure when the standard value of the drag coefficient is halved or doubled. Changing the drag coefficient provides insight into unbalanced effects in the boundary layer and their impact on the vortex evolution and structure. The changes in vortex behavior with changing drag coefficient are qualitatively similar for all schemes, the maximum intensification occurring for a value somewhere near the standard value of the drag coefficient. The interpretation given to explain this behavior underlines the intrinsically unbalanced nature of the boundary-layer dynamics although, for reasons discussed, a complete theory for the behavior does not exist. The behavior found is at odds with the predictions of Emanuel’s (balance) theory for the maximum intensity of a tropical cyclone, which predicts a monotonic decrease in intensity with the drag coefficient if the enthalpy exchange coefficient is held fixed. It is at odds also with a recent numerical study of the maximum intensity by Bryan and Rotunno. The study underscores the importance of boundary-layer dynamics in models for forecasting tropical-cyclone intensity and the need for care in choosing a boundary-layer scheme. However, it is not yet known which boundary-layer formulation is the most appropriate for this purpose, highlighting the need for a concerted research effort in this direction.

The recent studies of the sensitivity of tropical-cyclone intensification to the surface drag coefficient in a three-dimensional model by Montgomery et al. and Smith et al. are extended to include perturbations of the surface drag coefficient in one of four boundary layer parameterization schemes: the Bulk scheme, the Blackadar scheme, the MRF scheme, and the Gayno-Seaman scheme. The schemes are slightly modified to have the same drag coefficient formulation and the same constant exchange coefficients for sensible heat and moisture. We find that the intensification rate and mature intensity when the drag coefficient is perturbed randomly by variations of up to 60 percent are essentially unaltered. The results, in conjunction with an analysis of coherent drag coefficient variations for a moving vortex, challenge the notion that coupled wind-wave models are necessary to accurately forecast tropical cyclone intensification and mature intensity.

Wavenumber-1 wind speed asymmetries in 35 hurricanes are quantified in terms of amplitude and phase, based on aircraft observations from 128 individual flights between 1998 and 2011. The impacts of motion and 850-200 mb environmental vertical shear are examined separately to estimate the resulting asymmetric structures at the sea surface and standard 700 mb reconnaissance flight level. The surface asymmetry amplitude is on average around 50% smaller than found at flight level, and while the asymmetry amplitude grows in proportion to storm translation speed at the flight level, no significant growth at the surface is observed, contrary to conventional assumption. However, a significant upwind storm motion-relative phase rotation is found at the surface as translation speed increases, while the flight-level phase remains fairly constant. After removing the estimated impact of storm motion on the asymmetry, a significant residual shear direction-relative asymmetry is found, particularly at the surface, and on average is located down-shear to left-of-shear. Furthermore, the shear-relative phase has a significant downwind rotation as shear magnitude increases, such that the maximum rotates from the downshear to left-of-shear azimuthal location. By stratifying observations according to shear-relative motion, this general pattern of a left-of-shear residual wind speed maximum is found regardless of the orientation between the storm’s heading and shear direction. These results are quite consistent with recent observational studies relating Western Pacific typhoon wind asymmetries to environmental shear. Finally, changes in wind asymmetry over a five-day period in Hurricane Earl (2010) are analyzed to understand combined impacts of motion and the evolving shear.

Recent studies have shown the importance of accounting for model physics uncertainty within probabilistic forecasts. Attempts have been made at quantifying this uncertainty in terms of microphysical parameters such as fall speed coefficients, moments of hydrometeor particle size distributions and hydrometeor densities. It has been found that uncertainty in terms of these “traditional” microphysical parameters is highly non-Gaussian, calling into question the possibility of estimating and propagating this error using Gaussian statistical techniques such as as ensemble Kalman methods. Here, a new choice of uncertain control variables is proposed which instead considers uncertainty in individual modeled microphysical processes. These “process parameters” are multiplicative perturbations on contributions of individual modeled microphysical processes to hydrometeor time tendency. The new process parameters provide a natural and appealing choice for the quantification of aleatory microphysical parameterization uncertainty. Results of a non-linear Monte Carlo parameter estimation experiment for these new process parameters are presented and compared with the results using traditional microphysical parameters as uncertain control variables. Both experiments occur within the context of an idealized one-dimensional simulation of moist convection, under the observational constraint of simulated radar reflectivity. Results indicate that the new process parameters have a more Gaussian character compared with traditional microphysical parameters, likely due to a more linear control on observable model evolution. In addition, posterior forecast distributions using the new control variables (process parameters) are shown to have less bias and variance. These results strongly recommend the use of the new process parameters for an Ensemble Kalman-based estimation of microphysical parameterization uncertainty.

In this study, a new Multi-Scale Intensity (MSI) metric for evaluating Tropical Cyclone (TC) intensity forecasts is presented. The metric consists of the resolvable and observable, low wavenumber intensity represented by the sum of amplitudes of azimuthal wavenumbers 0 and 1 for wind speed within the TC vortex at the radius of maximum wind, and a stochastic residual, all determined at 10 meter elevation. The residual wind speed is defined as the difference between an estimate of maximum speed and the low wavenumber intensity. The MSI metric is compared to the standard metric that includes only the maximum speed. Using Stepped Frequency Microwave Radiometer wind speed observations from TC aircraft reconnaissance to estimate the low wavenumber intensity and the National Hurricane Center’s Best Track (BT) intensity for the maximum wind speed estimate, it is shown that the residual intensity is well represented as a stochastic quantity with small mean, standard deviation and absolute norm values that are within the expected uncertainty of the BT estimates. The result strongly suggests that the practical predictability of TC intensity is determined by the observable and resolvable low wavenumber intensity within the vortex. Verification of a set of high resolution numerical forecasts using the MSI metric demonstrates that this metric provides more informative and more realistic estimates of the intensity forecast errors. It is also shown that the maximum speed metric allows for error compensation between the low wavenumber and residual intensities, which could lead to forecast skill over-estimation and inaccurate assessment of the impact of forecast system change on the skill.

The NOAA Wide Swath Radar Altimeter (WSRA) uses 80 narrow beams spread over ±30° in the cross-track direction to generate raster lines of sea surface topography at a 10 Hz rate from which sea surface directional wave spectra are produced. A ±14° subset of the backscattered power data associated with the topography measurements is used to produce independent measurements of rain rate and sea surface mean square slope at 10 s intervals. Theoretical calculations of rain attenuation at the WSRA 16.15 GHz operating frequency using measured drop size distributions for both mostly convective and mostly stratiform rainfall demonstrate that the WSRA absorption technique for rain determination is relatively insensitive to both ambient temperature and the characteristics of the drop size distribution, in contrast to reflectivity techniques. The variation of the sea surface radar reflectivity in the vicinity of a hurricane is reviewed. Fluctuations in the sea surface scattering characteristics caused by changes in wind speed or the rain impinging on the surface cannot contaminate the rain measurement because they are calibrated out using the WSRA measurement of mean square slope. WSRA rain measurements from a NOAA WP-3D hurricane research aircraft off the North Carolina coast in Hurricane Irene on 26 August 2011 are compared with those from the Stepped Frequency Microwave Radiometer (SFMR) on the aircraft and the NEXRAD National Mosaic and Multi-Sensor Quantitative Precipitation Estimation (QPE) System.

This study presents a new approach for retrieving hurricane surface wind vectors utilizing C-band dual-polarization (VV, VH) synthetic aperture radar (SAR) observations. The co-polarized geophysical model function (CMOD5.N) and a new cross-polarized wind speed retrieval model for dual-polarization (C-2POD) are employed to construct a cost function. Minimization of the cost function allows optimum estimates for the wind speeds and directions. The wind direction ambiguities are removed using a parametric two dimensional sea-surface inflow angle model. To evaluate the accuracy of the proposed method, two RADARSAT-2 SAR images of Hurricanes Bill and Bertha are analyzed. The retrieved wind speeds and directions are compared with collocated QuikSCAT scatterometer winds, showing good consistency. Results suggest that the proposed method has good potential to retrieve hurricane surface wind vectors from dual-polarization SAR observations.

No abstract.

A storm-relative data assimilation method for tropical cyclones is introduced for the ensemble Kalman filter, using the Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS) developed at the Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory at the National Oceanic and Atmospheric Administration. The method entails translating tropical cyclone observations to storm-relative coordinates and requires the assumption of simultaneity of all observations. The observations are then randomly re-distributed to assimilation cycles to achieve a more homogeneous spatial distribution. A proof-of-concept study is carried out in an observing system simulation experiment in which airborne Doppler radar radial wind observations are simulated from a higher-resolution (4.5/1.5 km) version of the same model. The results here are compared to the Earth-relative version of HEDAS. When storm-relative observations are assimilated using the original HEDAS configuration, improvements are observed in the kinematic representation of the tropical cyclone vortex in analyses. The use of the storm-relative observations with a more homogeneous spatial distribution also reveals that a reduction of the covariance localization horizontal length scale by 1/2 to ~120 km provides the greatest incremental improvements. Potential positive impact is also seen in the slower cycle-to-cycle error growth. Spatially smoother analyses are obtained in the horizontal and the evolution of the azimuthally averaged wind structure during short-range forecasts demonstrates better consistency with the nature run.

The Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS) is developed to assimilate tropical cyclone inner-core observations for high-resolution vortex initialization. It is based on a serial implementation of the square-root ensemble Kalman filter (EnKF). In this study, HWRF is used in an experimental configuration with horizontal grid spacing of 9/3 km on the outer/inner domains. HEDAS is applied to 83 cases from years 2008-2011. With the exception of two Hurricane Hilary (2011) cases in the eastern North Pacific basin, all cases are observed in the Atlantic basin. Observed storm intensity for these cases ranges from tropical depression to category-4 hurricane. Overall, it is found that high-resolution tropical cyclone observations, when assimilated with an advanced data assimilation technique such as the EnKF, result in analyses of the primary circulation that are realistic in terms of intensity, wavenumber-0 radial structure, as well as wavenumber-1 azimuthal structure. Representing the secondary circulation in the analyses is found to be more challenging with systematic errors in the magnitude and depth of the low-level radial inflow. This is believed to result from a model bias in the experimental HWRF due to the over-diffusive nature of the planetary boundary layer parameterization utilized. Thermodynamic deviations from the observed structure are believed to be due to both an imbalance between the number of the kinematic and thermodynamic observations in general and the sub-optimal ensemble covariances between kinematic and thermodynamic fields. Future plans are discussed to address these challenges.

Here we show, from in situ aircraft measurements in the hurricane boundary layer, a height-dependent transition of the flow from 3-D to 2-D turbulence. This marks a fundamental change in the energy dynamics of the hurricane boundary layer due to the fact that in 3-D, energy flows downscale from larger to smaller scales, whereas in 2-D, it flows upscale, from smaller to larger scales. These results represent the first measurement of the 2-D upscale energy flux in the atmosphere and also the first to characterize the transition from 3-D to 2-D. It is shown that the large-scale parent vortex may gain energy directly from small scales in tropical cyclones.

Recent enhancements to the tropical cyclone-buoy database (TCBD) have incorporated data from the Extended Best Track (EBT) and the Statistical Hurricane Intensity Prediction Scheme (SHIPS) archive for tropical cyclones between 1975 and 2007. This information is used to analyze the relationships between large-scale atmospheric parameters, radial and shear-relative air-sea structure, and intensity change in strengthening and weakening hurricanes. Observations from this research illustrate that the direction of the large-scale vertical wind shear at mid-to-low levels can impact atmospheric moisture conditions found near the surface. Drier low-level environments were associated with northerly shear conditions. In a separate analysis comparing strengthening and weakening hurricanes, drier surface conditions were also found for the intensifying sample. Since SST conditions were similar for both groups of storms, it is likely that the atmosphere was primarily responsible for modifying the near-surface thermodynamic environment (and ultimately surface moisture flux conditions) for this particular analysis. 

This paper presents an approach using the GEneralized Nonlinear Retrieval Analysis (GENRA) tool and general inverse theory diagnostics including the maximum likelihood solution and the Shannon information content to investigate the performance of a new spectral technique for the retrieval of cloud optical properties from surface based transmittance measurements. The cumulative retrieval information over broad ranges in cloud optical thickness (τ), droplet effective radius (r_e), and overhead sun angles is quantified under two conditions known to impact transmitted radiation; the variability in land surface albedo and atmospheric water vapor content. Our conclusions are: (1) the retrieved cloud properties are more sensitive to the natural variability in land surface albedo than to water vapor content; (2) the new spectral technique is more accurate (but still imprecise) than a standard approach, in particular for τ between 5 and 60 and r_e less than approximately 20 μm; and (3) the retrieved cloud properties are dependent on sun angle for clouds of from 5 to 10 and r_e < 10 μm, with maximum sensitivity obtained for an overhead sun.

This review of new understanding and forecasting of tropical cyclones (TCs) is based on presentations at the International Top-level Forum on Rapid Change Phenomena in Tropical Cyclones in Haikou, China. The major topics are the sudden changes in tracks, rapid changes in structure and intensity, rapid changes in rainfall, and advances in forecasting and forecaster requirements. Although improved track forecast guidance has been achieved with the Australian ACCESS-TC model and in track forecasts to 120 h by the China Meteorological Administration, there is a continuing need for better understanding and improved track forecast guidance. Advances in understanding of processes related to rapid intensification (RI), secondary eyewall formation, mechanisms controlling inner-core structure and size changes, and structure and intensity changes at landfall have been achieved, but progress in prediction of rapid changes in structure and intensity has been slow. Taking into account complex interactions involved in TC-related rainfall, a prioritized list of physical processes that govern rainfall from landfalling TCs in China has been developed. While forecaster participants were generally encouraged by the progress being made, they expressed a strong desire for a transition of that new knowledge to timely and reliable forecast guidance products.

Over the decade prior to 2007, the increasing vulnerability of the US to damage and economic disruption from tropical storms/hurricanes was dramatically demonstrated by the impacts of a number of land-falling storms. In 2008, the National Oceanic and Atmospheric Administration established the Hurricane Forecast Improvement Project (HFIP) to significantly increase the Agency's capability to address this vulnerability and begin to mitigate the impacts. In fiscal year 2009, The White House amended the President's Budget and Congress appropriated funding to achieve a 20% reduction in forecast error (track and intensity) in 5 years with 50% reduction in 10 years. Over the past 3 years, HFIP has built computational infrastructure and implemented a focused set of cross-organizational R&D activities to develop, demonstrate, and implement enhanced operational modeling capabilities to improve the numerical forecast guidance made available to the National Hurricane Center (NHC). HFIP collaborators, including federal laboratories and academic partners, have demonstrated potential for dramatic improvements in both hurricane track and intensity (up to 40%) prediction through the application of new techniques including improved data assimilation, higher resolution models (global and regional), enhanced model physics, better use of existing data sources to initialize regional hurricane models, and new post processing techniques. During each Hurricane Season, HFIP will run an experimental forecast system on NOAA's R&D high performance computing to provide experimental improved guidance to NHC forecasters. Prior to each season, NHC will review and select a set of enhanced guidance products to evaluate operationally during the season (mid July-October).

The characteristics of tropical cyclone vertical wind profiles and their associated wind speed peaks below 1.5 km were examined through the use of a large number of GPS dropwindsondes (GPS sondes) and radar-derived velocity azimuth display (VAD) profiles. Composite wind profiles were generated to document the mean structure of tropical cyclone vertical wind profiles and their changes with storm-relative position. Composite profiles were observed to change as radius decreased inward toward the radius of maximum winds. Profiles also varied between three azimuthal sectors. At landfall, wind profiles exhibited changes with radial distance and differences were observed between those within offshore and onshore flow regimes. The observations support a general reduction in boundary layer depth with decreasing radial distance. Wind profiles with peaks at low altitudes were typically confined to radii less than 60 km, near and radially inward from the radius of maximum winds. Wind speed maxima, when scaled by a layer mean wind, decreased in magnitude as radius decreased. At landfall, composite profiles showed a distinct low-level wind speed maximum in the eyewall region with significant differences between the onshore and offshore flow regimes.

The Hurricane Weather Research and Forecasting (HWRF) system was used in an idealized framework to gain a fundamental understanding of the variability in TC structure and intensity prediction that may arise due to vertical diffusion. The modeling system uses the Medium-Range Forecast (MRF) parameterization scheme. Flight-level data collected by a NOAA WP-3D research aircraft during the eyewall penetration of category 5 Hurricane Hugo (1989) at an altitude of about 450-500 m and Hurricane Allen (1980) were used as the basis to best match the modeled eddy diffusivities with wind speed. While reduction of the eddy diffusivity to a quarter of its original value produced the best match with the observations, such a reduction revealed a significant decrease in the height of the inflow layer as well which, in turn, drastically impacted the size and intensity changes in the modeled TC. The cross-isobaric flow (inflow) was observed to be stronger with the decrease in the inflow depth. Stronger inflow not only increased the spin of the storm, enhancing the generalized Coriolis term in the equations of motion for tangential velocity, but also resulted in enhanced equivalent potential temperature in the boundary layer, a stronger and warmer core and, subsequently, a stronger storm. More importantly, rapid acceleration of the inflow not only produced a stronger outflow at the top of the inflow layer, more consistent with observations, but also a smaller inner core that was less than half the size of the original.

The Desroziers diagnostics (DD) are applied to the cross-calibrated, multi-platform (CCMP) ocean surface wind data sets to estimate wind speed errors of the ECMWF background, the microwave satellite observations and the resulting CCMP analysis. The DD confirm that the ECMWF operational surface wind speed error standard deviations vary with latitude in the range 0.8–1.3 m s⁻¹ and that the cross-calibrated Remote Sensing Systems (RSS) wind speed retrievals standard deviations are in the range 0.5–0.7 m s⁻¹. Further the estimated CCMP analysis wind speed standard deviations are in the range 0.2–0.3 m s⁻¹. The results suggest the need to revise the parameterization of the errors due to the FGAT (first guess at the appropriate time) procedure. Errors for wind speeds −1 are homogeneous, but for the relatively rare, but critical higher wind speed situations, errors are much larger.

Hurricane Ike (2008) made landfall near Galveston, Texas, as a moderate intensity storm. Its large wind field in conjunction with the Louisiana-Texas coastline's broad shelf and large scale concave geometry generated waves and surge that impacted over 1000 km of coastline. Ike's complex and varied wave and surge response physics included: the capture of surge by the protruding Mississippi River Delta; the strong influence of wave radiation stress gradients on the Delta adjacent to the shelf break; the development of strong wind driven shore-parallel currents and the associated geostrophic setup; the forced early rise of water in coastal bays and lakes facilitating inland surge penetration; the propagation of a free wave along the southern Texas shelf; shore-normal peak wind-driven surge; and resonant and reflected long waves across a wide continental shelf. Preexisting and rapidly deployed instrumentation provided the most comprehensive hurricane response data of any previous hurricane. More than 94 wave parameter time histories, 523 water level time histories, and 206 high water marks were collected throughout the Gulf in deep water, along the nearshore, and up to 65 km inland. Ike's highly varied physics were simulated using SWAN + ADCIRC, a tightly coupled wave and circulation model, on SL18TX33, a new unstructured mesh of the Gulf of Mexico, Caribbean Sea, and western Atlantic Ocean with high resolution of the Gulf's coastal floodplain from Alabama to the Texas-Mexico border. A comprehensive validation was made of the model's ability to capture the varied physics in the system.

Since the first intentional acquisition of GPS signals reflected from water bodies, one of the objectives which has driven the research is to determine whether the acquired signal can provide useful geophysical information about the reflecting surface. One obvious condition of considerable interest is ocean surface wind speed. Theory suggested that the reflection technique, a form of bistatic RADAR, would be sensitive to surface roughness which in turn is driven by wind speed. This paper reports the results derived from data acquired over the past decade of applying the GPS reflection technique to ocean surface winds, particularly ocean surface winds in tropical cyclones. Examples of wind speed retrievals will be given for some illustrative cases of hurricanes and tropical storms. The results from several hurricanes and tropical storms on how the signal was calibrated will be presented. In addition, a quantitative comparison will be given between dropsondes deployed by NOAA during the storms and GPS reflection derived wind speeds taken at the same time. Conditions in which the GPS technique offers excellent comparisons as well as examples where the comparison is not so good will be presented. Suggestions will be given as to when the GPS technique can be used with confidence and when it is likely to be at variance with other methods.

A Gulf of Mexico performance evaluation and comparison of coastal circulation and wave models was executed through harmonic analyses of tidal simulations, hindcasts of Hurricane Ike (2008) and Rita (2005), and a benchmarking study. Three unstructured coastal circulation models (ADCIRC, FVCOM, and SELFE) validated with similar skill on a new common Gulf scale mesh (ULLR) with identical frictional parameterization and forcing for the tidal validation and hurricane hindcasts. Coupled circulation and wave models, SWAN+ADCIRC and WWMII+SELFE, along with FVCOM loosely coupled with SWAN, also validated with similar skill. NOAA's official operational forecast storm surge model (SLOSH) was implemented on local and Gulf scale meshes with the same wind stress and pressure forcing used by the unstructured models for hindcasts of Ike and Rita. SLOSH's local meshes failed to capture regional processes such as Ike's forerunner and the results from the Gulf scale mesh further suggest shortcomings may be due to a combination of poor mesh resolution, missing internal physics such as tides and nonlinear advection, and SLOSH's internal frictional parameterization. In addition, these models were benchmarked to assess and compare execution speed and scalability for a prototypical operational simulation. It was apparent that a higher number of computational cores are needed for the unstructured models to meet similar operational implementation requirements to SLOSH, and that some of them could benefit from improved parallelization and faster execution speed.

In 2008, the Canadian Space Agency sponsored the RADARSAT Hurricane Applications Project (RHAP), for researching new developments in the application of RADARSAT-1 synthetic aperture radar (SAR) data and innovative mapping approaches to better understand the dynamics of tropical cyclone genesis, morphology, and movement. Although tropical cyclones can be detected by many remote sensors, SAR can yield high-resolution (sub kilometer) and low-level storm information that cannot be seen below the clouds by other sensors. In addition to the wind field and tropical cyclone eye information, structures associated with atmospheric processes can also be detected by SAR. We have acquired 161 RADARSAT-1 SAR images through RHAP between 2001 and 2007. Among these, 73 images show clear tropical cyclone eye structure. In addition, we also acquired 10 images from the European Space Agency's ENVISAT SAR between 2004 and 2010. Both Atlantic hurricanes and Pacific typhoons are included. In this study, we analyze these 83 (73 RADARSAT-1 and 10 ENVISAT) images with tropical cyclone eye information along with ancillary tropical cyclone intensity information from the archive to generate tropical cyclone morphology statistics. Histograms of wave number asymmetry and intensity are presented. The statistics show that when the storm has higher intensity, the tropical cyclone eye tends to become more symmetric, and the area of the tropical cyclone eye, defined by the minimum wind area, tends to be smaller. Examples of fine-scale structures within the tropical cyclone, i.e., eye-eyewall meso-vortices, arc clouds, double eyewalls, and abnormally high wind or rain within eyes, are presented and discussed.

Both atmospheric gravity waves (AGW) and marine atmospheric boundary layer (MABL) rolls are simultaneously observed on an Envisat Advanced Synthetic Aperture Radar (ASAR) image acquired along the China coast on May 22, 2005. The Synthetic Aperture Radar (SAR) image covers about 400 by 400 km of a coastal area of the Yellow Sea. The sea surface imprints of AGW show the patterns of both a transverse wave along the coastal plain and a diverging wave in the lee of Mountain Laoshan (1133 m peak), which indicates that terrain forcing affects the formation of AGW. The AGW have a wavelength of 8-10 km and extend about 100 km offshore. Model simulation shows that these waves have amplitude over 3 km. Finer scale (~ 2 km) brush-like roughness features perpendicular to the coast are also observed and they are interpreted as MABL rolls. The FFT analysis shows that the roll wavelengths vary spatially. The two-way interactive, triply nested grid (9/3/1 km) Weather Research and Forecasting (WRF) model simulation reproduces AGW-generated wind perturbations which are in phase at all levels reaching up to the 700 mb level for the diverging AGW and the 900 mb level for the transverse AGW. The WRF simulation also reveals that dynamic instability, rather than thermodynamic instability, is the cause for the MABL roll generation. Differences in atmospheric inflection-point level and instability at different locations are reasons why the roll wavelengths vary spatially.

The Hurricane Research Division Doppler radar analysis software provides three-dimensional analyses of the three wind components in tropical cyclones. Although this software has been used for over a decade, there has never been a complete and in-depth evaluation of the resulting analyses. The goal here is to provide an evaluation that will permit the best use of the analyses, but also to improve the software. To evaluate the software, analyses are produced from simulated radar data acquired from an output of a HWRF nature run and are compared against the model “truth” wind fields. Comparisons of the three components of the wind show that the software provides analyses of good quality. The tangential wind is best retrieved, exhibiting an overall small mean error of 0.5 m s⁻¹ at most levels and root-mean-squared error less than 2 m s⁻¹. The retrieval of the radial wind is also quite accurate, exhibiting comparable errors, although the accuracy of the tangential wind is generally better. Some degradation of the retrieval quality is observed at higher altitude, mainly due to sparser distribution of data in the model. The vertical component of the wind appears to be the most challenging to retrieve, but the software still provides acceptable results. The tropical cyclone mean azimuthal structure as well as wavenumber structure is found to be very well captured. Sources of errors inherent to airborne Doppler measurements as well as the effects of some the simplications used in the simulation methodology are also discussed.

In this paper we introduce the concept of Track Integrated Kinetic Energy (TIKE) as a measure of seasonal Atlantic tropical cyclone activity and applied to seasonal variability in the Atlantic. It is similar in concept to the more commonly used Accumulated Cyclone Energy (ACE) with an important difference that in TIKE we accumulate the Integrated Kinetic Energy (IKE) for the lifespan of the Atlantic tropical cyclone. The IKE is however computed by volume integrating the 10m level sustained winds of tropical strength or higher quadrant-by quadrant, while ACE uses the maximum sustained winds only without accounting for the structure of the storm. In effect TIKE accounts for the intensity, duration, and size of the tropical cyclones. In this research we have examined the seasonality and the interannual variations of the seasonal Atlantic TIKE over a period of 22 years from 1990-2011. We find that the Atlantic TIKE climatologically peaks in the month of September and the frequency of storms with the largest TIKE are highest in the eastern tropical Atlantic. The interannual variations of the Atlantic TIKE reveal that it is likely influenced by SST variations in the equatorial Pacific and in the Atlantic Oceans. The SST variations in the central equatorial Pacific are negatively correlated with the contemporaneous seasonal (June-November) TIKE. The size of the Atlantic Warm Pool (AWP) is positively correlated with seasonal TIKE.

Simulations are conducted with a cloud-resolving numerical model to examine the transformation of a weak incipient mid-level cyclonic vortex into a tropical cyclone. Results demonstrate that two distinct pathways are possible and that development along a particular pathway is sensitive to model physics and initial conditions. One pathway involves a steady increase of the surface winds to tropical cyclone strength as the radius of maximum winds gradually decreases. A notable feature of this evolution is the creation of small-scale lower tropospheric cyclonic vorticity anomalies by deep convective towers and subsequent merger and convergence by the low-level secondary circulation. The second pathway also begins with a strengthening low-level circulation, but eventually a significantly stronger mid-level circulation develops. Cyclogenesis occurs subsequently when a small-scale surface concentrated vortex forms abruptly near the center of the larger-scale circulation. The small-scale vortex is warm core throughout the troposphere and results in a fall in local surface pressure of a few millibars. It usually develops rapidly, undergoing a modest growth to form a small tropical cyclone. Many of the simulated systems approach or reach tropical cyclone strength prior to development of a prominent mid-level vortex so that the subsequent formation of a strong small-scale surface concentrated vortex in these cases could be considered intensification rather than genesis. Experiments are performed to investigate the dependence on the inclusion of the ice phase, radiation, the size and strength of the incipient mid-level vortex, the amount of moisture present in the initial vortex, and the sea surface temperature. Notably, as the sea surface temperature is raised, the likelihood of development along the second pathway is increased. This appears to be related to an increased production of ice. The sensitivity of the pathway taken to model physics and initial conditions revealed by these experiments raise the possibility that the solution to this initial value problem is near a bifurcation point. Future improvements to model parameterizations and more accurate observations of the transformation of disturbances to tropical cyclones should clarify the conditions that favor a particular pathway when starting from a mid-level vortex

A nature run is a critical component of an observing system simulation experiment (OSSE), which is a framework for evaluating the potential impact of additional observations, enhanced observing systems, or alternative data assimilation schemes toward improving numerical weather forecasts. The nature run is a period of simulated weather generated by a research-quality numerical model, from which synthetic observations are sampled and provided to the data assimilation system and forecast model. This paper describes the development and validation of a nature run that depicts the life cycle of a strong hurricane over the North Atlantic Ocean. For compatibility with related research projects, the hurricane nature run is generated by a regional model, the weather research and forecasting model (WRF), embedded within the Joint OSSE global nature run previously generated by the European Center for Medium-Range Weather Forecasting. The domain sizes, resolution, and physical parameterizations used in the WRF simulation are discussed, and the evolution of the storm from tropical wave to recurving hurricane is described. The realism of the simulated hurricane is evaluated by comparing the model output to composited data from real hurricanes obtained from both in situ and remotely sensed observations. These include the pressure-wind relationship, the kinematic and thermodynamic structure of the boundary layer, the size and outward slope of the radius of maximum winds, and contours of frequency by altitude diagrams of reflectivity and vertical velocity. The strengths and weaknesses of the nature run hurricane are discussed.

Testbeds have emerged as a critical mechanism linking weather research with forecasting operations. The U.S. Weather Research Program (USWRP) was formed in the 1990s to help identify key gaps in research related to major weather prediction problems and the role of observations and numerical models. This planning effort ultimately revealed the need for greater capacity and new approaches to improve the connectivity between the research and forecasting enterprise. Out of this developed the seeds for what is now termed “testbeds.” While many individual projects, and even more broadly the NOAA National Weather Service (NWS) Modernization, were successful in advancing weather prediction services, it was recognized that specific forecast problems warranted a more focused and elevated level of effort. The USWRP helped develop these concepts with science teams and provided seed funding for several of the testbeds described. Based on the varying NOAA mission requirements for forecasting, on differences in the organizational structure and methods used to provide those services, and on differences in the state of the science related to those forecast challenges, testbeds have taken on differing characteristics, strategies, and priorities. Current testbed efforts described have all emerged between 2000-2011 and focus on hurricanes (Joint Hurricane Testbed), precipitation (Hydrometeorology Testbed), satellite data assimilation (Joint Center for Satellite Data Assimilation), severe weather (Hazardous Weather Testbed), satellite data support for severe weather prediction (Short-term Prediction Research and Transition Center), mesoscale modeling (Developmental Testbed Center), climate forecast products (Climate Testbed), testing and evaluation of satellite capabilities (GOES-R Proving Ground), aviation applications (Aviation Weather Testbed), and observing system experiments (OSSE Testbed).

Following a recent demonstration of multi-case compositing of axisymmetric tropical cyclone (TC) structure derived from airborne Doppler radar measurements, we extend the analysis to the asymmetric structure using an unprecedented database from 75 TC flights. In particular, we examine the precipitation and kinematic asymmetry forced by the TC’s motion and interaction with vertical wind shear. We quantify for the first time the average magnitude and phase of the three-dimensional shear-relative kinematic asymmetry of observed TCs through a composite approach. The composite analysis confirms principal features of the shear-relative TC asymmetry documented in prior numerical and observational studies (e.g., downshear tilt, downshear-right convective initiation, and a downshear-left precipitation maximum). The statistical significance of the composite shear-relative structure is demonstrated through a stratification of cases by shear magnitude. The impact of storm motion on eyewall convective asymmetry appears to be subdominant to the much greater constraint placed by vertical wind shear on the organization of convection, in agreement with prior studies using lightning and precipitation data.

The formation of cloud droplets on aerosol particles, technically known as the activation of cloud condensation nuclei (CCN), is the fundamental process driving the interactions of aerosols with clouds and precipitation. The Intergovernmental Panel on Climate Change (IPCC) and the Decadal Survey indicate that the uncertainty in how clouds adjust to aerosol perturbations dominates the uncertainty in the overall quantification of the radiative forcing attributable to human activities. Measurements by current satellites allow the determination of crude profiles of cloud particle size, but not of the activated CCN that seed them. The Clouds, Hazards, and Aerosols Survey for Earth Researchers (CHASER) mission concept responds to the IPCC and Decadal Survey concerns, utilizing a new technique and high-heritage instruments to measure all the quantities necessary to produce the first global survey maps of activated CCN and the properties of the clouds associated with them. CHASER also determines the activated CCN concentration and cloud thermodynamic forcing simultaneously, allowing the effects of each to be distinguished.

Recent work has developed a new framework for the impact of vertical wind shear on the intensity evolution of tropical cyclones. A focus of this framework is on the frustration of the tropical cyclone's power machine by shear-induced, persistent downdrafts that flush relatively cool and dry (lower equivalent potential temperature, theta_e) air into the storm's inflow layer. These previous results have been based on idealized numerical experiments for which we have deliberately chosen a simple set of physical parameterizations. Before efforts are undertaken to test the proposed framework with real atmospheric data, we assess here the robustness of our previous results in a more realistic and representative experimental setup by surveying and diagnosing five additional numerical experiments. The modifications of the experimental setup comprise the values of the exchange coefficients of surface heat and momentum fluxes, the inclusion of experiments with ice microphysics, and the consideration of weaker, but still mature tropical cyclones. In all experiments, the depression of the inflow layer theta_e values is significant and all tropical cyclones exhibit the same general structural changes when interacting with the imposed vertical wind shear. Tropical cyclones in which strong downdrafts occur more frequently exhibit a more pronounced depression of inflow layer theta_e outside of the eyewall in our experiments. The magnitude of the theta_e depression underneath the eyewall early after shear is imposed in our experiments correlates well with the magnitude of the ensuing weakening of the respective tropical cyclone. Based on the evidence presented, it is concluded that the newly proposed framework is a robust description of intensity modification in our suite of experiments.

Differences in the inner-core structure of intensifying (IN; intensity increase of at least 20 kt /24 h) and steady-state (SS; intensity remaining between ± 10 kt/24 h) tropical cyclones (TC’s) are examined using composites of airborne Doppler observations collected from NOAA P-3 aircraft missions. The IN dataset contains 40 eyewall passes from 14 separate missions, while the SS dataset contains 53 eyewall passes from 14 separate missions. Intensifying TC’s have a ring-like vorticity structure inside the radius of maximum wind (RMW), lower vorticity in the outer core, a deeper, stronger inflow layer, and stronger axisymmetric eyewall upward motion compared with steady-state TC’s. There is little difference in the vortex tilt between 2 and 7 km, and both IN and SS TC’s show an eyewall precipitation and updraft asymmetry whose maxima are located in the downshear and downshear left region. The azimuthal coverage of eyewall and outer-core precipitation is greater for IN TC’s. There is little difference in the distribution of downdrafts and weak to moderate updrafts in the eyewall. The primary difference is seen at the high end of the vertical velocity spectrum, where IN TC’s have a larger number of convective bursts. These bursts accomplish more vertical mass flux, but they comprise such a small portion of the total vertical velocity distribution that there is little difference in the shape of the net mass flux profile. The radial location of convective bursts for IN TC’s is preferentially located inside the RMW, where the axisymmetric vorticity is generally higher, whereas for SS TC’s the bursts are located outside the RMW.

An update of the progress achieved as part of the NOAA Intensity Forecasting Experiment (IFEX) is provided. Included is a brief summary of the noteworthy aircraft missions flown in the years since 2005, the first year IFEX flights occurred, as well as a description of the research and development activities that directly address the three primary IFEX goals: (1) Collect observations that span the tropical cyclone (TC) life cycle in a variety of environments for model initialization and evaluation; (2) Develop and refine measurement strategies and technologies that provide improved real-time monitoring of TC intensity, structure, and environment; and (3) Improve the understanding of physical processes important in intensity change for a TC at all stages of its life cycle. Such activities include the real-time analysis and transmission of Doppler radar measurements; numerical model and data assimilation advancements; characterization of tropical cyclone composite structure across multiple scales, from vortex-scale to turbulence-scale; improvements in statistical prediction of rapid intensification; and studies specifically targeting tropical cyclogenesis, extratropical transition, and the impact of environmental humidity on TC structure and evolution. While progress in TC intensity forecasting remains challenging, the activities described here provide some hope for improvement. 

In a previous paper, Judt and Chen proposed that secondary eyewall formation can be the result of the accumulation of convectively generated potential vorticity in the rainbands. They argue that secondary potential vorticity maxima precede the development of the secondary wind maximum and conclude that vortex Rossby waves do not contribute to the formation of the secondary eyewall. Amidst examination of their thought-provoking study, some questions arose regarding their methodology, interpretation, and portrayal of previous literature. Here the authors inquire about aspects of the methodology for diagnosing vortex Rossby waves and assessing their impact on their simulation. Inaccuracies in the literature review are noted and further analysis of existing, three-dimensional, full-physics, numerical hurricane integrations that exhibit canonical secondary eyewalls are encouraged.

In this second part of a two-part study, details of the upper-ocean response within an idealized baroclinic current to a translating tropical cyclone are examined in a series of non-linear, reduced-gravity numerical simulations. Based on observations obtained as part of joint NOAA-NSF experiment in Hurricane Lili (2002), the pre-existing ocean mass and momentum fields are initialized with a Gulf of Mexico Loop Current-like jet, which is subsequently forced by a vortex whose wind stress field approximates that observed in the Lili experiments. Due to (1) favorable coupling between the wind stress and pre-existing current vectors and (2) wind-driven currents flowing across the large horizontal pressure gradient, wind energy transfer to the mixed layer can be more efficient in such a regime as compared to the case of an initially horizontally homogeneous ocean. However, nearly all energy is removed by advection and wave flux by two local inertial periods after storm passage, consistent with the observational results. Experiments are performed to quantify differences in one-dimensional and three-dimensional linearized approximations to the full model equations. In addition, sensitivity experiments to variations in the initial geostrophic current structure are performed to develop a parameter space over which a significant energy response could optimally be observed.

In this study the properties and causes of systematic errors in high-resolution data assimilation of inner core tropical cyclone (TC) observations were investigated using the HWRF Ensemble Data Assimilation System (HEDAS). Although Aksoy et al. (2012b) demonstrated overall good performance of HEDAS for 83 cases from years 2008-2011 using airborne observations from research and operational aircraft, some systematic errors were identified in the analyses with respect to independent observation-based estimates. The axisymmetric primary circulation intensity was underestimated for hurricane cases and the secondary circulation was systematically weaker for all cases. The diagnostic analysis in this study shows that the underestimate of primary circulation was caused by the systematic spin down of the vortex core in the short term forecasts during the cycling with observations. This tendency bias was associated with the systematic errors in the secondary circulation, temperature and humidity. The biases were reoccurring in each cycle during the assimilation due to inconsistency between the strength of primary and secondary circulation during the short-term forecasts, the impact of model error in planetary boundary layer dynamics, and the effect of forecast tendency bias on the background error correlations. Although limited to the current analysis the findings in this study point to a generic problem of mutual dependence of short-term forecast tendency and state estimate errors in the data assimilation of TC core observations. The results indicate that such coupling of errors in the assimilation would also lead to short term intensity forecast bias after the assimilation for the same reasons.

Super Typhoon Saomai (2006, 08W), which caused historical disaster in the landfall region, is the most powerful typhoon ever making landfall in Mainland China since 1949. The impact of Tropical Storm Bopha (2006, 10W) on Saomai is regarded as a binary tropical cyclone (TC) interaction. In order to quantify the influence of Bopha on the intensity of Saomai, a set of numerical experiments are performed by artificially modifying the intensity of Bopha in its initial conditions. It is shown that changing the intensity of Bopha has significant effects on simulating Saomai’s intensities, structures, and tracks. We find that moisture transport is a pivotal process of binary TC interaction. It is interesting that there are opposite effects by Bopha at different development stages of Saomai. The existence of Bopha and increasing its intensity would weaken Saomai at its intensifying stage while intensifying Saomai at its weakening stage. A possible explanation of these effects is the direction change of moisture transport from/to Saomai at its intensifying/weakening stages through the channel. It may suggest a significant relevance for operational intensity forecasts under active binary TC interaction.

This study investigates the asymmetric structure of the hurricane boundary layer in relation to the environmental vertical wind shear in the inner core region. Data from 1878 GPS dropsondes deployed by research aircraft in 19 hurricanes are analyzed in a composite framework. Kinematic structure analyses based on Doppler radar data from 75 flights are compared with the dropsonde composites. Shear-relative quadrant-mean composite analyses show that both the kinematic and thermodynamic boundary-layer height scales tend to decrease with decreasing radius, consistent with previous axisymmetric analyses. There is still a clear separation between the kinematic and thermodynamic boundary-layer heights. Both the thermodynamic mixed layer and height of maximum tangential wind speed are within the inflow layer. The inflow layer depth is found to be deeper in quadrants down shear, with the downshear right (DR) quadrant being the deepest. The mixed layer depth and height of maximum tangential wind speed are alike at the eyewall, but are deeper outside in quadrants left of the shear. The results also suggest that air parcels acquire equivalent potential temperature (θ_e) from surface fluxes as they rotate through the upshear right (UR) quadrant from the upshear left (UL) quadrant. Convection is triggered in the DR quadrant in the presence of asymmetric mesoscale lifting coincident with a maximum in θ_e. Energy is then released by latent heating in the downshear left (DL) quadrant. Convective downdrafts bring down cool and dry air to the surface and lower θ_e again in the DL and UL quadrants. This cycling process may be directly tied to shear-induced asymmetry of convection in hurricanes.

Within the National Oceanic and Atmospheric Administration, the Hurricane Research Division of the Atlantic Oceanographic and Meteorological Laboratory has developed the Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS) to assimilate hurricane inner-core observations for high-resolution vortex initialization. HEDAS is based on a serial implementation of the square root ensemble Kalman filter. HWRF is configured with a horizontal grid spacing of 9/3 km on the outer/inner domains. In this preliminary study, airborne Doppler radar radial wind observations are simulated from a higher-resolution (4.5/1.5 km) version of the same model with other modifications that resulted in appreciable model error. A 24-h nature run simulation of Hurricane Paloma is initialized at 7 November 2008 12Z and produced a realistic, category-2-strength hurricane vortex. The impact of assimilating Doppler wind observations is assessed in observation space as well as in model space. It is observed that while the assimilation of Doppler wind observations results in significant improvements in the overall vortex structure, a general bias in the average error statistics persists due to the under-estimation of overall intensity. A general deficiency in ensemble spread is also evident. While covariance inflation/relaxation and observation thinning result in improved ensemble spread, these do not translate into improvements in overall error statistics. These results strongly suggest a need to include in the ensemble a representation of forecast error growth from other sources such as model error.

This paper describes a realistic computer simulation of airborne hurricane surveillance using the recently developed microwave remote sensor, the hurricane imaging radiometer (HIRAD). An end-to-end simulation is described of HIRAD wind speed and rain rate measurements during two hurricanes while flying on a high-altitude aircraft. This simulation addresses the particular challenge which is accurate hurricane wind speed measurements in the presence of intense rain rates. The objective of this research is to develop baseline retrieval algorithms and provide a wind speed measurement accuracy assessment for future hurricane flights including the NASA GRIP hurricane field program that was conducted in summer of 2010. Examples of retrieved hurricane wind speed and rain rate images are presented, and comparisons of the retrieved parameters with two different numerical hurricane models data are made. Special emphasis is provided on the wind speed measurement error, and statistical results are presented over a broad range of wind and rain conditions over the full measurement swath (earth incidence angle).

A series of idealized experiments with the NOAA Experimental Hurricane Research and Forecasting Model (HWRFX) are performed to examine the sensitivity of idealized tropical cyclone (TC) intensification to various parameterization schemes of the boundary layer, subgrid convection, cloud microphysics and radiation. Results from all the experiments are compared in terms of the maximum surface 10-m wind (VMAX) and minimum sea level pressure (PMIN), operational metrics of TC intensity, as well as the azimuthally-averaged temporal and spatial structure of the tangential wind and its material acceleration. The conventional metrics of TC intensity (VMAX and PMIN) are found to be insufficient to reveal the sensitivity of the simulated TC to variations in model physics. Comparisons of the sensitivity runs indicate that (1) different boundary layer (BL) physics parameterization schemes for vertical sub-grid turbulence mixing lead to differences not only in the intensity evolution in terms of the VMAX and PMIN, but also in the structural characteristics of the simulated tropical cyclone; (2) the surface drag coefficient is a key parameter that controls the VMAX-PMIN relationship near the surface; and (3) different microphysics and subgrid convection parameterization schemes, due to their different realizations of diabatic heating distribution, lead to significant variations in the vortex structure. The quantitative aspects of these results indicate that the current uncertainties in the BL mixing, surface drag, microphysics parameterization schemes have comparable impacts on the intensity and structure of simulated TCs. The results indicate also that there is a need to include structural parameters in the HWRFX model evaluation.

Quantifying air-sea exchanges of enthalpy and momentum is important for understanding and skillfully predicting tropical cyclone intensity, but the magnitude of the corresponding wind-speed-dependent bulk exchange coefficients is largely unknown at major hurricane wind speeds greater than 50 m s^-1. Since direct turbulent flux measurements in these conditions are extremely difficult, the momentum and enthalpy fluxes were respectively deduced via absolute angular momentum and total energy budgets. An error analysis of the methodology was performed to quantify and mitigate potentially significant uncertainties resulting from unresolved budget terms and observational errors. An analysis of six missions from the 2003 CBLAST field program in major hurricanes Fabian and Isabel was conducted using a new variational technique. The analysis indicates a near-surface mean drag coefficient (CD) of 2.4 x 10^-3 with a 46% standard deviation and a mean enthalpy coefficient (CK) of 1.0 x 10^-3 with a 40% standard deviation for wind speeds between 52 and 72 m s^-1. These are the first known estimates of CK and the ratio of enthalpy to drag coefficient (CK/CD) in major hurricanes. The results suggest that there is no significant change in the magnitude of the bulk exchange coefficients estimated at minimal hurricane wind speeds, and that the ratio CK/CD does not significantly increase for wind speeds greater than 50 m s^-1.

Multi-platform observations of Hurricane Rita (2005) were collected as part of the Hurricane Rainband and Intensity Change (RAINEX) field campaign during a concentric eyewall stage of the storm's lifecycle that occurred from 21-22 September. Satellite, aircraft, dropwindsonde, and Doppler radar data are used here to examine the symmetric evolution of the hurricane as it underwent eyewall replacement. During the approximately one day observation period, developing convection associated with the secondary eyewall became more symmetric and contracted inwards. Latent heating in the emergent secondary eyewall led to the development of a distinct toroidal (overturning) circulation with inertially-constrained radial inflow above the boundary layer and compensating subsidence in the moat region, properties that are consistent broadly with the balanced vortex response to an imposed ring of diabatic heating outside the primary eyewall. The primary eyewall's convection became more asymmetric during the observation period, but the primary eyewall was still the dominant swirling wind and vorticity structure throughout the period. The observed structure and evolution of Rita's secondary eyewall suggest that spin up of the tangential winds occurred both within and above the boundary layer, and that both balanced and unbalanced dynamical processes played an important role. Although Rita's core intensity decreased during the observation period, the observations indicate a 125% increase in areal extent of hurricane force winds and a 19% increase in integrated kinetic energy resulting from the eyewall replacement.

Liquid water content (g m^-3), precipitation rate (mm hr-¹) and radar reflectivity (dBZ) are inferred from cross-sections of particle images obtained by aircraft. Each data set is presented in a probability format to display changing functional relationships for the selected intervals. The probability of intercepting a given quantity during a flight provides guidance in required instrument sensitivity together with the frequency of precipitation and liquid water content events for given rainfall totals. These data are compared with surface rain rate obtained over two years in the May-October warm seasons in Miami, Florida with a hotplate rain gauge. The warm season Miami surface rain rate probability distribution is similar to the 2005 hurricane rain rate distribution. Rain rates > ~120 mm hr^-1 were responsible for over half of the accumulation, even though lighter rain dominated by time. Hurricane rainfall is somewhat more intense than the normal surface convective rainfall in that 10% of the 1977-2001 (old) hurricane rain rates exceeded 20 mm hr-¹, whereas only 10% of the surface rain rates exceeded only ~10 mm hr^-1. The shape of the rain rate probability distributions from the 2005 (recent) hurricane data were nearly identical to the probability distribution of rain rates in the Miami, FL data. The radar reflectivity distributions were similar, whose 90% level was about 45 dBZ for the old storms, and about 35 dBZ for the 2005 storms. These data clearly show the low bias of the 2005 hurricane data caused by the systematic avoidance of heavy precipitation.

The Shannon information content provides an objective measure of the information in a data set. In this paper, we quantify the information content of hyperspectral liquid water cloud measurements over a spectral range (300-2500 nm) representing approximately 95% of the total energy in the solar spectrum. We also use the Shannon information content to analyze the cloud retrieval wavelengths and weightings used by the Solar Spectral Flux Radiometer (SSFR) and to determine the cumulative information in the SSFR retrieval. These applications illustrate the utility of the Shannon information content in guiding the effective processing of hyperspectral data. Such efficiency is of growing importance considering the push toward spectrally resolved satellite measurements of reflected solar irradiance used to study climate.

The HRD Real-time Hurricane Wind Analysis System (H*Wind) is a software application used by NOAA's Hurricane Research Division to create a gridded tropical cyclone wind analysis based on a wide range of observations. These analyses are used in both forecasting and research applications. Although mean bias and RMS errors are listed, H*Wind lacks robust uncertainty information that considers the contributions of random observation errors, relative biases between observation types, temporal drift resulting from combining non-simultaneous measurements into a single analysis, and smoothing and interpolation errors introduced by the H*Wind analysis. This investigation seeks to estimate the total contributions of these sources, and thereby provide an overall uncertainty estimate for the H*Wind product. A series of statistical analyses show that in general, the total uncertainty in the H*Wind product in hurricanes is approximately 6% near the storm center, increasing to nearly 13% near the tropical storm force wind radius. The H*Wind analysis algorithm is found to introduce a positive bias to the wind speeds near the storm center, where the analyzed wind speeds are enhanced to match the highest observations. In addition, spectral analyses are performed to ensure that the filter wavelength of the final analysis product matches user specifications. With increased knowledge of bias and uncertainty sources and their effects, researchers will have a better understanding of the uncertainty in the H*Wind product, and can then judge the suitability of H*Wind for various research applications.

Over the last decade substantial improvements have been made in our ability to observe the tropical cyclone boundary layer. Low-level wind speed maxima have been frequently observed in Global Positioning System dropwindsonde (GPS sonde) profiles. Data from GPS sondes and coastal Doppler radars were employed to evaluate the characteristics of tropical cyclone vertical wind profiles in open ocean conditions and at landfall. Changes to the mean vertical wind profile were observed azimuthally and with decreasing radial distance toward the cyclone center. Wind profiles within the hurricane boundary layer exhibited a logarithmic increase with height up to the depth of the wind maximum.

This paper provides an account of the performance of an experimental version of the Hurricane Weather Research and Forecasting system (HWRFX) for 87 cases of Atlantic tropical cyclones during the 2005, 2007, and 2009 hurricane seasons. The HWRFX system was used to study the influence of model grid resolution, initial conditions, and physics. The model was run with two versions of horizontal resolution; (i) a parent domain at a resolution of about 27 km with a 9 km moving nest (27:9) (consistent with the current operational resolution) and (ii) a parent domain at a resolution of 9 km with a 3 km moving nest (9:3). The 9:3 configuration is the first step in testing the impact of finer resolutions for future versions of the operational model. The two configurations were run with initial conditions for tropical cyclones obtained from the operational Geophysical Fluid Dynamics Laboratory (GFDL) and HWRF models. Sensitivity experiments were also conducted with the physical parameterization scheme. The study shows that the 9:3 HWRFX system using GFDL initial conditions and a system of physics similar to the operational version (HWRF) provides the best results in terms of both track and intensity prediction. Use of the HWRF initial conditions in HWRFX model provides reasonable skill, when used in cases with initially strong storms (hurricane strength). However, initially weak storms (below hurricane strength) posed special challenges for the models. For the weaker storm cases, none of the predictions from the HWRFX runs or the operational GFDL forecasts provided any consistent improvement when compared to the statistical-dynamical intensity model (Decay-SHIPS).

The main historical archive of all tropical storms, subtropical storms, and hurricanes in the North Atlantic Ocean, Caribbean Sea, and Gulf of Mexico from 1851 to the present is known as the Atlantic hurricane database (HURDAT), which is the fundamental database for meteorological, engineering, and financial studies of these cyclones. Previous work has demonstrated that a reanalysis of HURDAT is necessary because it contains many random errors and systematic biases. The Atlantic Hurricane Reanalysis Project is an ongoing effort to correct the errors in HURDAT and to make HURDAT as accurate a database as possible with utilization of all available data. For this study, HURDAT is reanalyzed for the period 1944-53, the first decade of the "aircraft reconnaissance era." The track and intensity of each existing tropical cyclone in HURDAT are reassessed, and previously unrecognized tropical cyclones are discovered, analyzed, and recommended to the HURDAT Best Track Change Committee for inclusion into HURDAT (existing tropical cyclones may be removed from the database as well if analyses indicate evidence that no tropical storm existed). Changes to the number of tropical storms, hurricanes, major hurricanes, accumulated cyclone energy, and U.S. landfalling hurricanes are recommended for most years of the decade. Estimates of uncertainty in the reanalyzed database for the decade are also provided.

Waves breaking at the ocean surface are important to the dynamical, chemical, and biological processes at the air-sea interface. The traditional view is that the white capping and aero-dynamical surface roughness increase with wind speed up to a limiting value. This view is fundamental to hurricane forecasting and climate research but it has never been verified at extreme winds. Here we show with observations that at high wind speeds white caps remain constant and at still higher wind speeds are joined, and increasingly dominated, by streaks of foam and spray. At surface wind speeds of ~40 m/s the streaks merge into a white out, the roughness begins to decrease and a high-velocity surface jet begins to develop. The roughness reduces to virtually zero by ~80 m/s wind speed, rendering the surface aero-dynamically extremely smooth in the most intense part of extreme (or major) hurricanes (wind speed > 50 m/s). A preliminary assessment shows that cross swell, dominant in large regions of hurricanes, allows the roughness under high wind conditions to increase considerably before it reduces to the same low values.

In Part I of this study, the association between the secondary eyewall formation (SEF) and the broadening of the outer swirling wind in Typhoon Sinlaku (2008) was documented. The findings from Part I help lay the groundwork for the application of a newly proposed intensification paradigm to SEF. Part II presents a new model for SEF that utilizes this new paradigm and its axisymmetric view of the dynamics. The findings point to a sequence of structure changes that occur in the vortex's outer-core region, culminating in SEF. The sequence begins with a broadening of the tangential winds, followed by an increase of the corresponding boundary layer (BL) inflow and an enhancement of convergence in the BL where the secondary eyewall forms. The narrow region of strong BL convergence is associated with the generation of supergradient winds in and just above the BL that acts to rapidly decelerate inflow there. The progressive strengthening of BL inflow and the generation of an effective adverse radial force therein leads to an eruption of air from the BL to support convection outside the primary eyewall in a favorable thermodynamic/kinematic environment. The results suggest that the unbalanced response in the BL serves as an important mechanism for initiating and sustaining a ring of deep convection in a narrow supergradient wind zone outside the primary eyewall. This progressive BL control on SEF suggests that the BL scheme and its coupling to the interior flow need to be adequately represented in numerical models to improve the prediction of SEF timing and preferred location.

Observations from the NASA 10 cm polarimetric Doppler weather radar (NPOL) were used to examine structure, development, and oceanic transition of West African Mesoscale Convective Systems (MCSs) during the NASA African Monsoon Multidisciplinary Analysis (NAMMA) to determine possible indicators leading to downstream tropical cyclogenesis. Characteristics examined from the NPOL data include echo-top heights, maximum radar reflectivity, height of maximum radar reflectivity, and convective and stratiform coverage areas. Atmospheric radiosondes launched during NAMMA were used to investigate environmental stability characteristics that the MCSs encountered while over land and ocean, respectively. Strengths of African Easterly Waves (AEWs) were examined along with the MCSs in order to improve the analysis of MCS characteristics. Mean structural and environmental characteristics were calculated for systems that produced TCs and for those that did not in order to determine differences between the two types. Echo-top heights were similar between the two types, but maximum reflectivity and height and coverage of intense convection (>50 dBZ) are all larger than for the TC producing cases. Striking differences in environmental conditions related to future TC formation include stronger African Easterly Jet, increased moisture especially at middle and upper levels, and increased stability as the MCSs coastally transition.

While tropical cyclones (TCs) usually decay after landfall, Tropical Storm Fay (2008) initially developed a storm central eye over South Florida by anomalous intensification over land. Unique to the Florida peninsula are Lake Okeechobee and the Everglades, which may have provided a surface feedback as the TC tracked near these features around the time of peak intensity. Analysis is done with the use of an ensemble model-based approach with the Developmental Testbed Center (DTC) version of the Hurricane WRF (HWRF) model using an outer domain and a storm-centered moving nest with 27- and 9-km grid spacing, respectively. Choice of land surface parameterization and small-scale surface features may influence TC structure, dictate the rate of TC decay, and even the anomalous intensification after landfall in model experiments. Results indicate that the HWRF model track and intensity forecasts are sensitive to three features in the model framework: land surface parameterization, initial boundary conditions, and the choice of planetary boundary layer (PBL) scheme. Land surface parameterizations such as the Geophysical Fluid Dynamics Laboratory (GFDL) Slab and Noah land surface models (LSMs) dominate the changes in storm track, while initial conditions and PBL schemes cause the largest changes in the TC intensity over land. Land surface heterogeneity in Florida from removing surface features in model simulations shows a small role in the forecast intensity change with no substantial alterations to TC track.

Performing wavenumber decomposition on azimuthally-distributed data such as those in tropical cyclones can be challenging when data gaps exist in the signal. In the literature, one usually finds ad hoc approaches to determine maximum gap size beyond which not to perform Fourier decomposition. The goal of the present study is to provide a more objective and systematic method to choose the maximum gap size allowed to perform a Fourier analysis on observational data. A Monte-Carlo-type experiment is conducted where signals of various wavenumber configurations are generated with gaps of varying size, then a simple interpolation scheme is applied and Fourier decomposition is performed. The wavenumber decomposition is evaluated in a way that requires retrieval of at least 80% of the original amplitude with less than 20° phase shift. Maximum allowable gap size is then retrieved for wavenumbers 0-2. When prior assessment of signal configuration is available, we believe that the present study can provide valuable guidance for gap size beyond which Fourier decomposition is not advisable.

Tropical cyclones are one of the deadliest and costliest weather phenomena worldwide. As a killer, tropical cyclones are far ahead of many other natural disasters. The word "cyclone" was coined in 1848 by Henry Piddington, British meteorologist, and is derived from the Greek word "kuklos," i.e., the coil of a snake as the air flow of the storm resembles it. The nomenclature of tropical cyclones is different in different parts of the world. In the Atlantic and eastern Pacific, they are known as hurricanes and in the western Pacific as typhoons. In the Indian region, they are simply known as tropical cyclones. Almost all of these storms form within 25° latitude on both sides of the equator except over the 5°N to 5°S equatorial region.

Analyses of thermodynamic data gathered from airborne dropwindsondes during the Tropical Cyclone Structure (2008) experiment are presented for the disturbance that became Typhoon Nuri. Although previous work has suggested that Nuri formed within the protective recirculating "pouch" region of a westward propagating wave-like disturbance and implicated rotating deep convective clouds in driving the inflow to spin up the tangential circulation of the system-scale flow, the nature of the thermodynamic environment that supported the genesis remains a topic of debate. During the genesis phase, vertical profiles of virtual potential temperature show little variability between soundings on a particular day and the system-average soundings likewise show a negligible change. There is a tendency also for the lower and middle troposphere to moisten. However, the data show that, on the scale of the recirculating region of the disturbance, there was no noticeable reduction of virtual temperature in the lower troposphere, but a small warming (less than 1 K) in the upper troposphere. Vertical profiles of pseudo-equivalent potential temperature, theta_e, during the genesis show a modestly decreasing deficit of theta_e in the vertical between the surface and the height of minimum θe (between 3 and 4 km), from 17.5 K to 15.2 K. The findings reported here are consistent with those found for developing disturbances observed in the Pre-Depression Investigation of Cloud Systems in the Tropics (PREDICT) experiment in 2010. Some implications of the findings are discussed.

The principal hypotheses of a new model of tropical cyclogenesis, known as the marsupial paradigm, were tested in the context of Atlantic tropical disturbances during the National Science Foundation (NSF)-sponsored Pre-Depression Investigation of Cloud Systems in the Tropics (PREDICT) experiment in 2010. PREDICT was part of a tri-agency collaboration, along with the National Aeronautics and Space Administration's Genesis and Rapid Intensification Processes (NASA GRIP) experiment and the National Oceanic and Atmospheric Administration's Intensity Forecasting Experiment (NOAA IFEX), intended to examine both developing and nondeveloping tropical disturbances. During PREDICT, a total of 26 missions were flown with the NSF/NCAR Gulfstream V (GV) aircraft sampling eight tropical disturbances. Among these were four cases (Fiona, ex-Gaston, Karl, and Matthew) for which three or more missions were conducted, many on consecutive days. Because of the scientific focus on the Lagrangian nature of the tropical cyclogenesis process, a wave-relative frame of reference was adopted throughout the experiment in which various model- and satellite-based products were examined to guide aircraft planning and real-time operations. Here, the scientific products and examples of data collected are highlighted for several of the disturbances. The suite of cases observed represents arguably the most comprehensive, self-consistent dataset ever collected on the environment and mesoscale structure of developing and nondeveloping predepression disturbances.

Tropical cyclone is one of the most devastating weather phenomena all over the world. The Environmental Modeling Center (EMC) of the National Center for Environmental Prediction (NCEP) has developed a sophisticated mesoscale model known as Hurricane Weather Research and Forecasting (HWRF) system for tropical cyclone studies. The state-of-the-art HWRF model (atmospheric component) has been used in simulating most of the features our present study of a very severe tropical cyclone "Mala", which developed on April 26 over the Bay of Bengal and crossed the Arakan coast of Myanmar on April 29, 2006. The initial and lateral boundary conditions are obtained from Global Forecast System (GFS) analysis and forecast fields of the NCEP, respectively. The performance of the model is evaluated with simulation of cyclone Mala with six different initial conditions at an interval of 12 h each from 00 UTC 25 April 2006 to 12 UTC 27 April 2006. The best result in terms of track and intensity forecast as obtained from different initial conditions is further investigated for large-scale fields and structure of the cyclone. For this purpose, a number of important predicted fields’ viz. central pressure/pressure drop, winds, precipitation, etc. are verified against observations/verification analysis. Also, some of the simulated diagnostic fields such as relative vorticity, pressure vertical velocity, heat fluxes, precipitation rate, and moisture convergences are investigated for understanding of the characteristics of the cyclone in more detail. The vector displacement errors in track forecasts are calculated with the estimated best track provided by the India Meteorological Department (IMD). The results indicate that the model is able to capture most of the features of cyclone Mala with reasonable accuracy.

The Joint Hurricane Testbed (JHT) is evaluated after its first decade. The JHT's impact on National Hurricane Center forecast operations, the testbed's highest rated research-to-operations projects, and its most significant challenges are described. The Joint Hurricane Testbed (JHT) is reviewed at the completion of its first decade. Views of the program by hurricane forecasters at the National Hurricane Center, the testbed's impact on forecast accuracy, and highlights of the top rated projects are presented. Key concerns encountered by the testbed are identified as possible "lessons learned" for future research-to-operations efforts. The paper concludes with thoughts on the potential changing role of the JHT.

This paper examines the structure and evolution of a mature tropical cyclone in vertical wind shear (VWS) using airborne Doppler radar observations of Hurricane Guillermo (1997). In Part I, the modulation of eyewall convection via the rotation of vorticity asymmetries through the downshear-left quadrant was documented during rapid intensification. Here, the focus is on the relationship between VWS, vortex tilt, and associated asymmetry within the tropical cyclone core region during two separate observation periods. A method for estimating local VWS and vortex tilt from radar datasets is further developed, and the resulting vertical structure and its evolution are subjected to statistical confidence tests. Guillermo was a highly resilient vortex, evidenced by its small tilt magnitude relative to the horizontal scale of the vortex core. The deep-layer tilt was statistically significant, oriented on average ~60° left of shear. Large-scale vorticity and thermal asymmetries oriented along the tilt direction support a response of Guillermo to shear forcing that is consistent with balanced dynamics. The time-averaged vertical motion asymmetry within the eyewall exhibited maximum ascent values ~40° left of the deep-layer shear, or in this case, right of the deep-layer tilt. The observation-based analysis of Guillermo's interaction with VWS confirms findings of recent theoretical and numerical studies, and serves as the basis for a more comprehensive investigation of VWS and tropical cyclone intensity change using a recently constructed multistorm database of Doppler radar analyses.

The multiscale inner-core structure of mature tropical cyclones is presented via the use of composites of airborne Doppler radar analyses. The structure of the axisymmetric vortex and the convective and turbulent-scale properties within this axisymmetric framework are shown to be consistent with many previous studies focusing on individual cases or using different airborne data sources. On the vortex scale, these structures include the primary and secondary circulations, eyewall slope, decay of the tangential wind with height, low-level inflow layer and region of enhanced outflow, radial variation of convective and stratiform reflectivity, eyewall vorticity and divergence fields, and rainband signatures in the radial wind, vertical velocity, vorticity, and divergence composite mean and variance fields. Statistics of convective-scale fields and how they vary as a function of proximity to the radius of maximum wind show that the inner eyewall edge is associated with stronger updrafts and higher reflectivity and vorticity in the mean and have broader distributions for these fields compared with the outer radii. In addition, the reflectivity shows a clear characteristic of stratiform precipitation in the outer radii and the vorticity distribution is much more positively skewed along the inner eyewall than it is in the outer radii. Composites of turbulent kinetic energy (TKE) show large values along the inner eyewall, in the hurricane boundary layer, and in a secondary region located at about 2-3 times the radius of maximum wind. This secondary peak in TKE is also consistent with a peak in divergence and in the variability of vorticity, and they suggest the presence of rainbands at this radial band.

The effect of sea spray on thermodynamics and microphysical structure of the hurricane boundary layer (HBL) under strong wind speed is investigated using a 2-D hybrid Lagrangian-Eulerian model with spectral bin microphysics. A large number of adjacent and interacting Lagrangian parcels move within a turbulent-like flow with largest vortices are being interpreted as large eddies (LE) with characteristic velocity of a few meters per seconds. It is shown that sea spray effect strongly depends on the environmental conditions, largely on relative humidity RH. In case the RH < ~ 90%, spray evaporates and contributes to moistening and cooling of the HBL, as well as to increase in surface fluxes. In case RH > ~ 90 RH% the effects of spray on the BL thermodynamics substantially decreases. Super-saturation at the upper levels leads to the formation of cloud drops on background aerosols. This high sensitivity is related to high salinity of spray drops. It is shown that LE transport about 20% of large spray drops with radius exceeding 150 μm to the upper levels in the HBL. It is hypothesized that this effect is of high importance as regards to the spray effect on microphysics and dynamics of deep convective clouds typical of hurricane eyewall.

The 2006 NASA-African Monsoon Multidisciplinary Analyses (NAMMA-06) field campaign examined a compact, low-level vortex embedded in the trough of an AEW between 9-12 September. The vortex triggered a squall line (SL) in southeastern Senegal in the early morning of 11 September and became Tropical Depression 8 on 12 September. During this period, there was a Saharan Air Layer (SAL) outbreak in northwestern Senegal and adjacent Atlantic Ocean waters in the proximity of the SL. Increases in aerosol optical thicknesses in Mbour, Senegal, high dewpoint depressions observed in the Kawsara and Dakar rawinsondes, and model back-trajectories suggest the SAL exists. The close proximity of this and SL suggests interaction through dust entrainment and precipitation invigoration.

Analyses of thermodynamic data gathered from airborne dropwindsondes released from the upper troposphere during the Pre-Depression Investigation of Cloud Systems in the Tropics (PREDICT) experiment are presented. We focus on two systems that finally became hurricanes Karl and Matthew, and one system (Gaston) that attained tropical storm status, but subsequently weakened and never redeveloped during five days of monitoring. Data for all events show that the largest values of total precipitable water are collocated with the surface trough and with values of convective available potential energy that seem high enough to support convective organization. These values coincide mostly with low values of convective inhibition. Vertical profiles of virtual potential temperature show little variability between soundings on a particular day, but the system means from day to day show a slight warming. In contrast, vertical profiles of pseudo-equivalent potential temperature, θ_e, show much more variability between soundings on a particular day on account of the variability in moisture. In all systems, there was is a tendency for the lower troposphere to moisten, but in the non-developing system, the troposphere became progressively drier in the height range between approximately 2 and 9 km during the five days of observations. In the developing systems, the troposphere moistened. The most prominent difference between the non-developing system and the two developing systems was the much larger reduction of θ_e between the surface and a height of 3 km, typically 25 K in the non-developing system, compared with only 17 K in the developing systems. Conventional wisdom would suggest that, for this reason, the convective downdraughts would be stronger in the non-developing system and would thereby act to suppress the development. Here we propose an alternative hypothesis in which the drier air weakens the convective updraughts and thereby the convective amplification of absolute vorticity necessary for development.

The maximum surface wind speed is an important parameter for tropical cyclone operational analysis and forecasting, since it defines the intensity of a cyclone. Operational forecast centers typically refer the wind speed to a maximum 1-min or 10-min averaged value. Aircraft reconnaissance provides measurements of surface winds, however due the large variation of winds in the eyewall, it remains unclear to what extent observing the maximum wind is limited by the sampling pattern. Estimating storm intensity as simply the maximum of the observed winds is generally assumed by forecasters to underestimate the true storm intensity. The work presented herein attempts to quantify this difference by applying a methodology borrowed from the observing system simulation experiment concept, in which simulated "observations" are drawn from a numerical model. These "observations" may then be compared to the actual peak wind speed of the simulation. By sampling a high-resolution numerical simulation of Hurricane Isabel (2003) with a virtual aircraft equipped with a stepped frequency microwave radiometer flying a standard "figure-4" pattern, we find the highest wind observed over a flight typically underestimates the 1-min averaged model wind speed by 8.5 ± 1.5%. In contrast, due to its corresponding larger spatial scale, the 10-min averaged maximum wind speed is far less underestimated (1.5 ± 1.7%) using the same sampling method. These results support the National Hurricane Center's practice which typically assumes that the peak 1-min wind is somewhat greater than the highest observed wind speed over a single reconnaissance aircraft mission.

The ocean mixed layer response to a tropical cyclone within, and immediately adjacent to, the Gulf of Mexico Loop Current is examined. In the first of a two-part study, a comprehensive set of temperature, salinity, and current profiles acquired from aircraft-deployed expendable probes is utilized to analyze the three-dimensional oceanic energy evolution in response to Hurricane Lili's (2002) passage. Mixed-layer temperature analyses show that the Loop Current cooled <1°C in response to the storm, in contrast to typically observed larger decreases of 3-5°C. Correspondingly, vertical current shear associated with mixed-layer currents, which is responsible for entrainment mixing of cooler water, was found to be up to 50% weaker, on average, than observed in previous studies within the directly-forced region. The Loop Current, which separates the warmer, lighter Caribbean Subtropical water from the cooler, heavier Gulf Common water, was found to decrease in intensity by -0.18 ± 0.25 m s^-1 over an approximately 10-day period within the mixed layer. Contrary to previous ocean response studies which have assumed approximately horizontally homogeneous ocean structure prior to storm passage, a kinetic energy loss of 5.8 ± 6.4 kJ m^-2, or approximately -1 wind stress-scaled energy unit, was observed. By examining nearsurface currents derived from satellite altimetry data, the Loop Current is found to vary similarly in magnitude over such time scales, suggesting storm-generated energy is rapidly removed by the pre-exiting Loop Current. In a future study, the simulated mixed-layer evolution to a Hurricane Lili-like storm within an idealized pre-existing baroclinic current is analyzed to help understand the complex air-sea interaction and resulting energetic response.

Uncertainty in cloud microphysical parameterization, a leading order contribution to numerical weather prediction error, is estimated using a Markov chain Monte Carlo (MCMC) algorithm. An inversion is performed on ten microphysical parameters using radar reflectivity observations with a vertically covarying error as the likelihood constraint. An idealized 1D atmospheric column model with prescribed forcing is used to simulate the microphysical behavior of a mid-latitude squall line. Novel diagnostics are employed for the probabilistic investigation of individual microphysical process behavior vis-a-vis parameter uncertainty. Uncertainty in the microphysical parameterization is presented via posterior probability density functions (PDFs) of parameters, observations, and microphysical processes. The results of this study show that radar reflectivity observations, as expected, provide a much stronger constraint on microphysical parameters than column-integral observations, in most cases reducing both the variance and bias in the maximum likelihood estimate of parameter values. This highlights the enhanced potential of radar reflectivity observations to provide information about microphysical processes within convective storm systems despite the presence of strongly nonlinear relationships within the microphysics model. The probabilistic analysis of parameterization uncertainty in terms of both parameter and process activity PDFs suggest the prospect of a stochastic representation of microphysical parameterization uncertainty; specifically, the results indicate that error may be more easily represented and estimated by microphysical process uncertainty rather than microphysical parameter uncertainty. In addition, these new methods of analysis allow for a detailed investigation of the full nonlinear and multivariate relationships between microphysical parameters, microphysical processes and radar observations.

In support of the NSF-PREDICT and NASA-GRIP Dry Run exercises and NOAA-IFEX during the 2009 hurricane season, a real-time wave tracking algorithm and corresponding diagnostic analyses based on a recently proposed tropical cyclogenesis model were applied to tropical easterly waves over the Atlantic. The model emphasizes the importance of a Lagrangian re-circulation region within a tropical wave critical layer (the so-called "pouch"), where persistent deep convection and vorticity aggregation as well as column moistening are favored for tropical cyclogenesis. Distinct scenarios of hybrid wave-vortex evolution are highlighted. It was found that easterly waves without a pouch or with a shallow pouch did not develop. Although not all waves with a deep pouch developed into a tropical storm, a deep wave pouch had formed prior to genesis for all the sixteen named storms originating from monochromatic easterly waves during the 2008 and 2009 seasons. On the other hand, the diagnosis of two non-developing waves with a deep pouch suggests that strong vertical shear or dry air intrusion at the middle to upper levels (where a wave pouch was absent) can disrupt deep convection and suppress storm development. To sum up, this study suggests that a deep wave pouch extending from the mid-troposphere (600~700 hPa) to near the surface is a necessary condition for tropical cyclone formation within an easterly wave. It is hypothesized also that a deep wave pouch together with other large-scale favorable conditions provides a sufficient condition for sustained convection and tropical cyclone formation. This hypothesized sufficient condition requires further testing and will be pursued in future work.

The prediction of tropical cyclone (TC) track has improved greatly in recent decades due in part to the implementation and improvement of numerical weather prediction (NWP) models. However, the prediction of TC intensity using NWP models remains difficult. Several hypotheses have been proposed to explain the factors contributing to the TC intensity prediction errors and one of the leading candidates is the implication of an evolving sea-surface temperature (SST) boundary condition beneath the TC. In this study, a regional scale coupled atmosphere-ocean model is developed using the Advanced Research Weather Research and Forecasting (ARW) model and the HYbrid Coordinate Ocean Model (HYCOM). A coupling algorithm and a methodology to define appropriate ocean initial conditions is provided. Experiments are conducted, during the lifecycle of TC Ike (2008), using both the coupled-model and static (e.g., temporally fixed) SST to illustrate the impacts of the coupled-model for the TC track, intensity, and structure, as well as upon the larger (synoptic) scale. The results from this study suggest that the impact of the evolving SST (e.g., from a coupled atmosphere-ocean model) begin to impact the intensity, size, and thermodynamic structure for TC Ike (2008) at forecast lead-times beyond 48-hours. Further, the forecast trajectories (i.e., tracks) do not illustrate large differences between the non- and coupled-models. Finally, the impact of the SST boundary condition upon TC Ike (2008) appears to be a function of the strength of the atmospheric forcing, in particular the size and intensity of the TC wind field.

In 2008, abundant dropwindsonde data were collected during both reconnaissance and surveillance flights in and around tropical cyclones (TCs) in the western North Pacific basin under the framework of the Observing System Research and Predictability Experiment (THORPEX) - Pacific Asian Regional Campaign (T-PARC). The National Centers for Environmental Prediction Global Forecast System (GFS) showed significant track improvements for Typhoon Sinlaku (2008) after the assimilation of dropwindsonde data. For this particular typhoon, the potential vorticity (PV) diagnosis is adopted to understand the key factors affecting the track. A data denial run initialized at 0000 UTC 10 September is examined to evaluate how the extra data collected during T-PARC improve GFS track forecasts. A quantitative analysis of the steering flow based on the PV diagnosis indicates that the Pacific subtropical high to the east of Sinlaku is a primary factor that advects Sinlaku northwestward, while the monsoon trough plays a secondary role. The assimilation of dropwindsonde data improves the structure and intensity of the initial vortex and maintains the forecast vortex structure in the vertical. The difference in the vertical extent of the vortices could be regarded as a cause for the discrepancy in steering flow between runs with and without the dropwindsonde data. This paper highlights the importance of improved analyses of the vertical TC structure, and thus of a representative steering flow in the deep troposphere during the forecasts.

In response to the needs of improving hurricane forecasts, we have built an experimental version of the operational Hurricane Weather Research and Forecasting Model (HWRF), which is based on the Weather Research and Forecasting Nonhydrostatic Mesoscale Model of the National Oceanic and Atmospheric Administration (NOAA). The experimental HWRF (HWRFx) is adopted to study the intensity change problem at the highest possible resolutions with the existing computing facility, using moving nests to focus the model resolution in the vicinity of the storms. Although this is at an early stage of development, results from real-time experiments in the 2008 hurricane season show that the HWRFx is generally comparable to the NOAA operational models, in terms of the accuracy of both track and intensity forecasts. The HWRFx, however, has a negative bias in the intensity forecasts as opposed to the positive biases of the NOAA operational models. We present in this article a brief description of the HWRFx and its performance during the 2008 hurricane season in comparison with the NOAA operational models.

This study presents an analysis of near-surface (10-m) inflow angles using wind vector data from over 1600 quality-controlled Global Positioning System dropwindsondes deployed by aircraft on 187 flights into 18 hurricanes. The mean inflow angle in hurricanes is found to be -22.6 ± 2.2° (95% confidence). Composite analysis results indicate little dependence of storm-relative axisymmetric inflow angle on local surface wind speed, and a weak but statistically-significant dependence on the radial distance from the storm center. A small, but statistically-significant dependence of the axisymmetric inflow angle on storm intensity, is also found, especially well outside the eyewall. By compositing observations according to radial and azimuthal location relative to storm motion direction, significant inflow angle asymmetries are found to depend on storm motion speed, although a large amount of unexplained variability remains. Generally, the largest storm-relative inflow angles (<-50°) are found in the fastest moving storms (> 8 m s^-1) at large radii (> 8 times the radius of maximum wind) in the right-front storm quadrant, while the smallest inflow angles (>-10°) are found in the fastest moving storms in the left-rear quadrant. Based on these observations, a parametric model of low-wavenumber inflow angle variability as a function of radius, azimuth, storm intensity, and motion speed, is developed. This model can be applied for purposes of ocean surface remote sensing studies when wind direction is either unknown or ambiguous, for forcing storm surge, surface wave, and ocean circulation models which require a parametric surface wind vector field, and evaluating surface wind field structure in numerical models of tropical cyclones.

This study examines further the characteristics of turbulent flow in the low-level region of intense hurricanes using in-situ aircraft observations. The data analyzed here are the flight-level data collected by research aircraft that penetrated the eyewalls of Category 5 Hurricane Hugo (1989), Category 4 Hurricane Allen (1980) and Category 5 Hurricane David (1979) between 1 km and the sea surface. Estimates of horizontal eddy momentum flux, horizontal eddy diffusivity, and horizontal mixing length are obtained. It is found that the horizontal momentum flux and horizontal diffusivity increase with increasing wind speed. The horizontal mixing length increases slightly with wind speed also, but the mixing length is not significantly dependent on the wind speed. The magnitude of the horizontal momentum flux is found to be comparable to that of the vertical momentum flux, indicating that horizontal mixing by turbulence becomes non-negligible in the hurricane boundary layer, especially in the eyewall region. Within the context of simple K-theory, the results suggest that the average horizontal eddy diffusivity and mixing length are approximately 1500 m² s^-1 and 750 m, respectively, at ~500 m in the eyewall region corresponding to the mean wind speed of approximately 52 m s^-1. It is recalled also that the mixing length is a virtual scale in numerical models, and is quantitatively smaller than the energy-containing scale of turbulent eddies. The distinction between these two scales is a useful reminder for the modeling community on the representation of small-scale turbulence in hurricanes.

Although vertical eddy diffusivity or viscosity has been extensively used in theoretical and numerical models simulating tropical cyclones, little observational study has documented the magnitude of the eddy diffusivity in high-wind conditions (>20 m s^-1) until now. Through analyzing in-situ aircraft data that were collected in the atmospheric boundary layer of four intense hurricanes, this study provides the first estimates of vertical distributions of the vertical eddy diffusivities for momentum, sensible heat, and latent heat flux in the surface wind speed range between 18-30 m s^-1. In this work, eddy diffusivity is determined from directly measured turbulent fluxes and vertical gradients of the mean variable, such as wind speed, temperature and humidity. The analyses show that the magnitudes of vertical eddy diffusivities for momentum and moisture fluxes are comparable to each other, but the eddy diffusivity for sensible heat flux is much smaller than that for the moisture flux. The vertical distributions of the eddy diffusivities are generally alike, increasing from the surface to a maximum value within the thermodynamic mixed layer then deceasing with height. The results indicate also that momentum and moisture are mainly transferred down gradient of the mean flow, while counter-gradient transport of the sensible heat may exist. The observational estimates are compared with the eddy diffusivities derived based on different methods as used in planetary boundary layer (PBL) parameterization schemes in numerical models, as well as ones used in previous observational studies.

As part of NOAA’s Hurricane Forecast Improvement Program (HFIP), this paper addresses the important role of aircraft observations in hurricane model physics validation and improvement. A model developmental framework for improving the physical parameterizations using quality-controlled and post- processed aircraft observations is presented, with steps that include model diagnostics, physics development, physics implementation, and further evaluation. Model deficiencies are first identified through model diagnostics by comparing the simulated axisymmetric multi-scale structures to observational composites. New physical parameterizations are developed in parallel based on in-situ observational data from specially designed hurricane field programs. The new physics package is then implemented in the model, which is followed by further evaluation. The developmental framework presented here is found to be successful in improving the surface layer and boundary layer parameterization schemes in the operational Hurricane Weather Research and Forecast (HWRF) model. Observations for improving physics packages other than boundary layer scheme are also discussed.

Four aircraft released dropwindsondes in and around tropical cyclones in the west Pacific during The Observing System Research and Predictability Experiment 2008 Pacific Area Regional Campaign and Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region; multiple aircraft concurrently participated in similar missions in the Atlantic. Previous studies have treated each region separately and have focused on the tropical cyclones whose environments were sampled. The large number of missions and tropical cyclones in both regions, and additional tropical cyclones in the east Pacific and Indian Oceans allows for the global impact of these observations on tropical cyclone track forecasts to be studied. The study shows that there are unintended global consequences to local changes in initial conditions, in this case due to the assimilation of dropwindsonde data in tropical cyclone environments. These global impacts are mainly due to the spectral nature of the model system. These differences should be small and slightly positive, since improved local initial conditions should lead to small global forecast improvements. However, the impacts on tropical cyclones far removed from the data are shown to be as large and positive as those on the tropical cyclones specifically targeted for improved track forecasts. Causes of this unexpected result are hypothesized, potentially providing operational forecasters tools to identify when large remote impacts from surveillance missions might occur.

In 1997, the National Oceanic and Atmospheric Administration's National Hurricane Center and the Hurricane Research Division began operational synoptic surveillance missions with the Gulfstream IV-SP jet aircraft to improve the numerical guidance for hurricanes that threaten the continental United States, Puerto Rico, the U.S. Virgin Islands, and Hawaii. The dropwindsonde observations from these missions were processed and formatted aboard the aircraft and sent to the National Centers for Environmental Prediction and the Global Telecommunications System to be ingested into the Global Forecasting System, which serves as initial and boundary conditions for regional numerical models that also forecast tropical cyclone track and intensity. As a result of limited aircraft resources, optimal observing strategies for these missions are investigated. An Observing System Experiment in which different configurations of the dropwindsonde data based on three targeting techniques (ensemble variance, ensemble transform Kalman filter, and total energy singular vectors) are assimilated into the model system was conducted. All three techniques show some promise in obtaining maximal forecast improvements while limiting flight time and expendables. The data taken within and around the regions specified by the total energy singular vectors provide the largest forecast improvements, though the sample size is too small to make any operational recommendations. Case studies show that the impact of dropwindsonde data obtained either outside of fully sampled, or within nonfully sampled target regions is generally, though not always, small; this suggests that the techniques are able to discern in which regions extra observations will impact the particular forecast.

The typhoon surveillance program Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) has been conducted since 2003 to obtain dropwindsonde observations around tropical cyclones near Taiwan. In addition, an international field project. The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) in which dropwindsonde observations were obtained by both surveillance and reconnaissance flights was conducted in summer 2008 in the same region. In this study, the impact of the dropwindsonde data on track forecasts is investigated for DOTSTAR (2003-09) and T-PARC (2008) experiments. Two operational global models from NCEP and ECMWF are used to evaluate the impact of dropwindsonde data. In addition, the impact on the two-model mean is assessed. The impact of dropwindsonde data on track forecasts is different in the NCEP and ECMWF model systems. Using the NCEP system, the assimilation of dropwindsonde data leads to improvements in 1- to 5-day track forecasts in about 60% of the cases. The differences between track forecasts with and without the dropwindsonde data are generally larger for cases in which the data improved the forecasts than in cases in which the forecasts were degraded. Overall, the mean 1- to 5-day track forecast error is reduced by about 10%-20% for both DOTSTAR and T-PARC cases in the NCEP system. In the ECMWF system, the impact is not as beneficial as in the NCEP system, likely because of more extensive use of satellite data and more complex data assimilation used in the former, leading to better performance even without dropwindsonde data. The stronger impacts of the dropwindsonde data are revealed for the 3- to 5-day forecast in the two-model mean of the NCEP and ECMWF systems than for each individual model.

Hurricane Gustav (2008) made landfall in southern Louisiana on 1 September 2008 with its eye never closer than 75 km to New Orleans, but its waves and storm surge threatened to flood the city. Easterly tropical-storm-strength winds impacted the region east of the Mississippi River for 12-15 h, allowing for early surge to develop up to 3.5 m there and enter the river and the city's navigation canals. During landfall, winds shifted from easterly to southerly, resulting in late surge development and propagation over more than 70 km of marshes on the river's west bank, over more than 40 km of Caernarvon marsh on the east bank, and into Lake Pontchartrain to the north. Wind waves with estimated significant heights of 15 m developed in the deep Gulf of Mexico but were reduced in size once they reached the continental shelf. The barrier islands further dissipated the waves, and locally generated seas existed behind these effective breaking zones. The hardening and innovative deployment of gauges since Hurricane Katrina (2005) resulted in a wealth of measured data for Gustav. A total of 39 wind wave time histories, 362 water level time histories, and 82 high water marks were available to describe the event. Computational models--including a structured-mesh deepwater wave model (WAM) and a nearshore steady-state wave (STWAVE) model, as well as an unstructured-mesh "simulating waves nearshore" (SWAN) wave model and an advanced circulation (ADCIRC) model--resolve the region with unprecedented levels of detail, with an unstructured mesh spacing of 100-200 m in the wave-breaking zones and 20-50 m in the small-scale channels. Data-assimilated winds were applied using NOAA's Hurricane Research Division Wind Analysis System (H*Wind) and Interactive Objective Kinematic Analysis (IOKA) procedures. Wave and surge computations from these models are validated comprehensively at the measurement locations ranging from the deep Gulf of Mexico and along the coast to the rivers and floodplains of southern Louisiana and are described and quantified within the context of the evolution of the storm.

The Jordan mean tropical sounding has provided a benchmark reference for representing the climatology of the tropical North Atlantic and Caribbean Sea atmosphere for over 50 years. However, recent observations and studies have suggested that during the months of the North Atlantic hurricane season, this region of the world is affected by multiple air masses with very distinct thermodynamic and kinematic characteristics. This study examined ~6,000 rawinsonde observations from the Caribbean Sea region taken during the core months (July-October) of the 1995-2002 hurricane seasons. It was found that single mean soundings created from this new dataset were very similar to Jordan's 1958 sounding work. However, recently developed multi-spectral satellite imagery that can track low- to mid-level dry air masses indicated that the 1995-2002 hurricane season dataset (and likely Jordan's dataset as well) was dominated by three distinct air masses: moist tropical (MT), Saharan Air Layer (SAL), and mid-latitude dry air intrusions (MLDAIs). Findings suggest that each sounding is associated with unique thermodynamic, kinematic, stability, and mean sea level pressure characteristics and that none of these soundings is particularly well-represented by a single mean sounding like Jordan's. This work presents three new mean tropical soundings (MT, SAL, and MLDAI) for the tropical North Atlantic Ocean and Caribbean Sea region and includes information on their temporal variability, thermodynamics, winds, wind shear, stability, total precipitable water, and mean sea level pressure attributes. It is concluded that the new MT, SAL, and MLDAI soundings presented here provide a more robust depiction of the tropical North Atlantic and Caribbean Sea atmosphere during the Atlantic hurricane season and should replace the Jordan mean tropical sounding as the new benchmark soundings for this part of the world.

Forecasting intensity changes in tropical cyclones (TCs) is a complex and challenging multiscale problem. While cloud-resolving numerical models using a horizontal grid resolution of 1-3 km are starting to show some skill in predicting the intensity changes in individual cases, it is not clear at this time what may be a reasonable horizontal resolution for forecasting TC intensity changes on a day-to-day-basis. The Experimental Hurricane Weather Research and Forecasting System (HWRFX) was used within an idealized framework to gain a fundamental understanding of the influence of horizontal grid resolution on the dynamics of TC vortex intensification in three dimensions. HWFRX is a version of the National Centers for Environmental Prediction (NCEP) Hurricane Weather Research and Forecasting (HWRF) model specifically adopted and developed jointly at NOAA's Atlantic Oceanographic and Meteorological Laboratory (AOML) and Earth System Research Laboratory (ESRL) for studying the intensity change problem at a model grid resolution of about 3 km. Based on a series of numerical experiments at the current operating resolution of about 9 km and at a finer resolution of about 3 km, it was found that improved resolution had very little impact on the initial spinup of the vortex. An initial axisymmetric vortex with a maximum wind speed of 20 m s^-1 rapidly intensified to 50 m s^-1 within about 24 h in either case. During the spinup process, buoyancy appears to have had a pivotal influence on the formation of the warm core and the subsequent rapid intensification of the modeled vortex. The high-resolution simulation at 3 km produced updrafts as large as 48 m s^-1. However, these extreme events were rare, and this study indicated that these events may not contribute significantly to rapid deepening. Additionally, although the structure of the buoyant plumes may differ at 9- and 3-km resolution, interestingly, the axisymmetric structure of the simulated TCs exhibited major similarities. Specifically, the similarities included a deep inflow layer extending up to about 2 km in height with a tangentially averaged maximum inflow velocity of about 12-15 m s^-1, vertical updrafts with an average velocity of about 2 m s^-1, and a very strong outflow produced at both resolutions for a mature storm. It was also found in either case that the spinup of the primary circulation occurred not only due to the weak inflow above the boundary layer but also due to the convergence of vorticity within the boundary layer. Nevertheless, the mature phase of the storm's evolution exhibited significantly different patterns of behavior at 9 and 3 km. While the minimum pressure at the end of 96 h was 934 hPa for the 9-km simulation, it was about 910 hPa for the 3-km run. The maximum tangential wind at that time showed a difference of about 10 m s^-1. Several sensitivity experiments related to the initial vortex intensity, initial radius of the maximum wind, and physics were performed. Based on ensembles of simulations, it appears that radial advection of the tangential wind and, consequently, radial flux of vorticity become important forcing terms in the momentum budget of the mature storm. Stronger convergence in the boundary layer leads to a larger transport of moisture fluxes and, subsequently, a stronger storm at higher resolution.

Despite the fact that latent heating in cloud systems drives many atmospheric circulations, including tropical cyclones, little is known of its magnitude and structure, largely because of inadequate observations. In this work, a reasonably high-resolution (2 km), four-dimensional airborne Doppler radar retrieval of the latent heat of condensation/evaporation is presented for rapidly intensifying Hurricane Guillermo (1997). Several advancements in the basic retrieval algorithm are shown, including (1) analyzing the scheme within the dynamically consistent framework of a numerical model, (2) identifying algorithm sensitivities through the use of ancillary data sources, and (3) developing a precipitation budget storage term parameterization. The determination of the saturation state is shown to be an important part of the algorithm for updrafts of ~5 m s^-1 or less. The uncertainties in the magnitude of the retrieved heating are dominated by errors in the vertical velocity. Using a combination of error propagation and Monte Carlo uncertainty techniques, biases are found to be small, and randomly distributed errors in the heating magnitude are ~16% for updrafts greater than 5 m s^-1 and ~156% for updrafts of 1 m s^-1. Even though errors in the vertical velocity can lead to large uncertainties in the latent heating field for small updrafts/downdrafts, in an integrated sense the errors are not as drastic. In Part II, the impact of the retrievals is assessed by inserting the heating into realistic numerical simulations at 2-km resolution and comparing the generated wind structure to the Doppler radar observations of Guillermo.

A large, unpredicted, water level increase appeared along a substantial section of the western Louisiana and northern Texas (LATEX) coasts 12-24 hrs in advance of the landfall of Hurricane Ike (2008), with water levels in some areas reaching 3 m above mean sea level. During this time the cyclonic wind field was largely shore parallel throughout the region. A similar early water level rise was reported for both the 1900 and the 1915 Galveston Hurricanes. The Ike forerunner anomaly occurred over a much larger area and prior to the primary coastal surge which was driven by onshore directed winds to the right of the storm track. We diagnose the forerunner surge as being generated by Ekman setup on the wide and shallow LATEX shelf. The longer forerunner time scale additionally served to increase water levels significantly in narrow-entranced coastal bays. The forerunner surge generated a freely propagating continental shelf wave with greater than 1.4 m peak elevation that travelled coherently along the coast to Southern Texas, and was 300 km in advance of the storm track at the time of landfall. This was, at some locations, the largest water level increase seen throughout the storm, and appears to be the largest freely-propagating shelf wave ever reported. Ekman setup-driven forerunners will be most significant on wide, shallow shelves subject to large wind fields, and need to be considered for planning and forecasting in these cases.

The purpose of this document is to provide an informed opinion on future climate scenarios relevant to Florida. It offers a primer on Florida's vulnerabilities to climate variability and change. The document is an excellent compilation of diverse viewpoints on future climate projection. It implores the readers to be cognizant of the associated uncertainty but not to use that as an excuse for inaction in climate adaptation and mitigation. Experts in diverse fields employed in institutions across Florida have contributed to this document and provided candid and informed assessments of future climate variation and change. The uniqueness of this document is that it broadens the discussion of a rather restrictive sounding title like "climate scenarios" to involve experts in sociology, environmental law, and economics, in addition to oceanography and meteorology. The earth's climate is a very complex system. Climate is intimately interrelated to many components of the earth system. However, climate is not limited to these interactions alone. It also includes the modulation of these interactions by external factors such as anthropogenic influence (or interference), volcanic eruptions, changes in solar activity, and changing planetary factors like orbital eccentricity, obliquity, and precession. Against this backdrop of complexity, this paper has tried to distill the information that is relevant to Florida. It is well understood that climate has no borders, and yet we focus here on Florida because of the huge demand for locally applicable information on climate change and variation. Therefore, time and again throughout this paper the impact of remote climate variations and change on Florida is emphasized. Finally this document provides some initial suggestions to further fortify our understanding of the impact of global climate change on Florida. The caveat however, is that these fledgling suggestions will have to be further molded by a developing synergy between the federal, state, private stakeholders and university researchers.

A plausible primary circulation and circulation center of a tropical cyclone (TC) can be deduced from a coastal Doppler radar using the ground-based velocity track display (GBVTD) technique and the GBVTD-simplex algorithm. The quality of the retrieved primary circulation is highly sensitive to the accuracy of the circulation center that can only be estimated from the degree of scattering of all possible centers obtained in GBVTD-simplex analyses from a single radar in real TCs. This study extends previous work to examine the uncertainties in the GBVTD-simplex-derived circulation centers and the GBVTD-derived primary circulations in Hurricane Danny (1997) sampled simultaneously from two Doppler radars [Weather Surveillance Radar-1988 Dopplers (WSR-88Ds) in Mobile, Alabama, and Slidell, Louisiana] for 5 h. It is found that the mean difference between the individually computed GBVTD-simplex-derived centers is 2.13 km, similar to the estimates in previous studies. This value can be improved to 1.59 km by imposing time continuity in the radius of maximum wind, maximum mean tangential wind, and the center position in successive volumes. These additional physical criteria, not considered in previous work, stabilized the GBVTD-simplex algorithm and paved the way for automating the center finding and wind retrieval procedures in the future. Using the improved set of centers, Danny's axisymmetric tangential wind structures retrieved from each radar showed general agreement with systematic differences (up to 6 m s^-1) in certain periods. The consistency in the wavenumber-1 tangential winds was not as good as their axisymmetric counterparts. It is suspected that the systematic differences in the axisymmetric tangential winds were caused by the unresolved wavenumber-2 sine components rather than from the relatively small cross-beam mean wind components in Danny.

Educators at all levels shared effective strategies for increasing the quality and quantity of education in the atmospheric and related sciences. Broad themes included a focus on collaboration, use of technology to enable learning, and strategies to get more atmospheric and related sciences into K-12 schools.

Assimilation of cloud-affected infrared radiances from the Geostationary Operational Environmental Satellite-8 (GOES-8) is performed using a four-dimensional variational data assimilation (4DVAR) system designated as the Regional Atmospheric Modeling Data Assimilation System (RAMDAS). A cloud mask is introduced in order to limit the assimilation to points that have the same type of cloud in the model and observations, increasing the linearity of the minimization problem. A series of experiments is performed to determine the sensitivity of the assimilation to factors such as the maximum-allowed residual in the assimilation, the magnitude of the background error decorrelation length for water variables, the length of the assimilation window, and the inclusion of other data such as ground-based data including data from the Atmospheric Emitted Radiance Interferometer (AERI), a microwave radiometer, radiosonde, and cloud radar. In addition, visible and near-infrared satellite data are included in a separate experiment. The assimilation results are validated using independent ground-based data. The introduction of the cloud mask where large residuals are allowed has the greatest positive impact on the assimilation. Extending the length of the assimilation window in conjunction with the use of the cloud mask results in a better-conditioned minimization, as well as a smoother response of the model state to the assimilation.

A major impediment to the intensity forecast of tropical cyclones (TCs) is believed to be associated with the interaction of TCs with dry environmental air. However, the conditions under which pronounced TC-environment interaction takes place are not well understood. As a step towards improving our understanding of this problem, we analyze here the flow topology of a TC immersed in an environment of vertical wind shear in an idealized, three-dimensional, convection-permitting numerical experiment. A set of distinct streamlines, the so-called manifolds, can be identified under the assumptions of steady and layer-wise horizontal flow. The manifolds are shown to divide the flow around the TC into distinct regions. The manifold structure in our numerical experiment is more complex than the well-known manifold structure of a non-divergent point vortex in uniform background flow. In particular, one manifold spirals inwards and ends in a limit cycle, a meso-scale dividing streamline encompassing the eyewall above the layer of strong inflow associated with surface friction and below the outflow layer in the upper troposphere. From the perspective of a steady and layer-wise horizontal flow model, the eyewall is well protected from the intrusion of environmental air. In order for the environmental air to intrude into the inner-core convection, time-dependent and/or vertical motions, which are prevalent in the TC inner-core, are necessary. Air with the highest values of moist-entropy resides within the limit cycle. This "moist envelope" is distorted considerably by the imposed vertical wind shear, and the shape of the moist envelope is closely related to the shape of the limit cycle. In a first approximation, the distribution of high- and low-theta_e air around the TC at low to mid-levels is governed by the stirring of convectively modified air by the steady, horizontal flow. Motivated by the results from the idealized numerical experiment, an analogue model based on a weakly divergent point vortex in background flow is formulated. The simple kinematic model captures the essence of many salient features of the manifold structure in the numerical experiment. A regime diagram representing realistic values of TC intensity and vertical wind shear can be constructed for the point-vortex model. The results indicate distinct scenarios of environmental interaction depending on the ratio of storm intensity and vertical-shear magnitude. Further implications of the new results derived from the manifold analysis for TCs in the real atmosphere are discussed.

Rapid intensification (RI) is difficult to forecast, but some progress has been made in developing probabilistic guidance for predicting these events. One such method is the RI index. The RI index is a probabilistic text product available to National Hurricane Center (NHC) forecasters in real time. The RI index gives the probabilities of three intensification rates [25, 30, and 35 kt (24 h)^-1; or 12.9, 15.4, and 18.0 m s^-1 (24 h)^-1] for the 24-h period commencing at the initial forecast time. In this study the authors attempt to develop a deterministic intensity forecast aid from the RI index and, then, implement it as part of a consensus intensity forecast (arithmetic mean of several deterministic intensity forecasts used in operations) that has been shown to generally have lower mean forecast errors than any of its members. The RI aid is constructed using the highest available RI index intensification rate available for probabilities at or above a given probability (i.e., a probability threshold). Results indicate that the higher the probability threshold is, the better the RI aid performs. The RI aid appears to outperform the consensus aids at about the 50% probability threshold. The RI aid also improves forecast errors of operational consensus aids starting with a probability threshold of 30% and reduces negative biases in the forecasts. The authors suggest a 40% threshold for producing the RI aid initially. The 40% threshold is available for approximately 8% of all verifying forecasts, produces approximately 4% reduction in mean forecast errors for the intensity consensus aids, and corrects the negative biases by approximately 15%-20%. In operations, the threshold could be moved up to maximize gains in skill (reducing availability) or moved down to maximize availability (reducing gains in skill).

At the time of the Deepwater Horizon oil rig explosion, the Loop Current (LC), a warm ocean current in the Gulf of Mexico (GoM), extended to 27.5°N just south of the rig. To measure the regional scale variability of the LC, oceanographic missions were flown on a NOAA WP-3D research aircraft to obtain ocean structural data during the spill and provide thermal structure profiles to ocean forecasters aiding in the oil spill disaster at 7 to 10 day intervals. The aircraft flew nine grid patterns over the eastern GoM between May and July 2010 deploying profilers to measure atmospheric and oceanic properties such as wind, humidity, temperature, salinity, and current. Ocean current profilers sampled as deep as 1500 m, conductivity, temperature, and depth profilers sampled to 1000 m, and bathythermographs sampled to either 350 or 800 m providing deep structural measurements. Profiler data were provided to modeling centers to predict possible trajectories of the oil and vector ships to regions of anomalous signals. In hindcast mode, assimilation of temperature profiles into the Hybrid Coordinate Ocean Model improved the fidelity of the simulations by reducing RMS errors by as much as 30% and decreasing model biases by half relative to the simulated thermal structure from models that assimilated only satellite data. The synoptic snapshots also provided insight into the evolving LC variability, captured the shedding of the warm core eddy Franklin, and measured the small-scale cyclones along the LC periphery.

We investigate the rotational constraint on the intensity and size of a tropical cyclones using a minimal, three-layer, axisymmetric tropical-cyclone model. In the first of two sets of experiments, the same initial baroclinic vortex is spun up in a quiescent environment with different levels of background rotation, characterized by the Coriolis parameter, f. It is found that the strongest vortices, as characterized by their final intensity, develop in environments with intermediate background rotation. It is found also that there exists a similar optimum background rotation strength to obtain the largest storm as measured by the radius of gale-force winds. These results appear to be in line with those of classical laboratory experiments by Turner and Lilly, an analogy that we explore in the present article. While the analogy is found to have certain limitations, including the fact that spin-up of the maximum tangential winds in the inner-core in the model takes place in the boundary layer, the study raises aspects of tropical-cyclone dynamics that we believe to be of fundamental importance and require further investigation. As an aid to understanding the foregoing results, a second set of calculations is carried out with the vortex forced by a prescribed radial profile of diabatic heating rate typical of that in the first set and with other moist processes excluded. For this distribution of heating rate, there is no optimum background rotation rate for intensity within a realistic range of values for f, implying that the relationship between the forcing strength and rotation strength is an important additional constraint in tropical cyclones. However, in these experiments, there is an optimum latitude for size, comparable with that in the first set of experiments. An interpretation is offered for these findings.

Rainfall on the subtropical east coast of Australia has declined at up to 50 mm per decade since 1970. Wavelet analysis is used to investigate eight station and four station-averaged rainfall distributions along Australia's subtropical east coast with respect to the El Niño-Southern Oscillation (ENSO), the inter-decadal Pacific oscillation (IPO), and the southern annular mode (SAM). The relationships are examined further using composite atmospheric circulation anomalies. Here we show that the greatest rainfall variability occurs in the 15-30 year periodicity of the 1948-1975 or "cool" phase of the IPO when the subtropical ridge is located sufficiently poleward for anomalous moist onshore airflow to occur together with high ENSO rainfall variability and high, negative phase, SAM variability. Thus, the mid-latitude westerlies are located at their most equatorward position in the Australian region. This maximizes tropospheric interaction of warm, moist tropical air with enhanced local baroclinicity over the east coast, and hence rainfall.

A unique data set of targeted dropsonde observations was collected during the THORPEX Pacific Asian Regional Campaign (T-PARC) in autumn 2008. The campaign was supplemented by an enhancement of the operational Dropsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) program. For the first time, up to four different aircraft were available for typhoon observations and over 1500 additional soundings were collected. This study investigates the influence of assimilating additional observations during the two major typhoon events of T-PARC on the typhoon track forecast by the global models of the European Centre for Medium-range Weather Forecasts (ECMWF), the Japan Meteorological Agency (JMA), the National Center for Environmental Prediction (NCEP) and the limited area Weather Research and Forecasting (WRF) model. Additionally, the influence of T-PARC observations on ECMWF mid-latitude forecasts is investigated. All models show an improving tendency of typhoon track forecasts, but the degree of improvement varied from about 20-40% in NCEP and WRF to a comparably low influence in ECMWF and JMA. This is likely related to lower track forecast errors without dropsondes in the latter two models, presumably caused by a more extensive use of satellite data and 4D-Var assimilation at ECMWF and JMA compared to 3D-Var of NCEP and WRF. The different behavior of the models emphasizes that the benefit gained strongly depends on the quality of the first-guess field and the assimilation system.

This study examines a hurricane prediction system that uses an ensemble Kalman filter (EnKF) to assimilate high-resolution airborne radar observations for convection-permitting hurricane initialization and forecasting. This system demonstrated very promising performance, especially on hurricane intensity forecasts, through experiments over all 61 applicable NOAA P-3 airborne Doppler missions during the 2008-2010 Atlantic hurricane seasons. The mean absolute intensity forecast errors initialized with the EnKF-analysis of the airborne Doppler observations at the 24- to 120-h lead forecast times were 20-40% lower than the National Hurricane Center's official forecasts issued at similar times. This prototype system was first implemented in real-time for Hurricane Ike (2008). It represents the first time that airborne Doppler radar observations were successfully assimilated in real-time into a hurricane prediction model. It also represents the first time that the convection-permitting ensemble analyses and forecasts for hurricanes were performed in real-time. Also unprecedented was the on-demand usage of more than 23,000 computer cluster processors simultaneously in real-time.

This study analyzes the flight-level data collected by research aircraft that penetrated the eyewalls of category 5 Hurricane Hugo (1989) and category 4 Hurricane Allen (1980) between 1 km and the sea surface. Estimates of turbulent momentum flux, turbulent kinetic energy (TKE), and vertical eddy diffusivity are obtained before and during the eyewall penetrations. Spatial scales of turbulent eddies are determined through a spectral analysis. The turbulence parameters estimated for the eyewall penetration leg are found to be nearly an order of magnitude larger than those for the leg outside the eyewall at similar altitudes. In the low-level intense eyewall region, the horizontal length scale of the dominant turbulent eddies is found to be between 500 and 3000 m, and the corresponding vertical length scale is approximately 100 m. The results suggest also that it is unwise to include eyewall vorticity maxima (EVM) in the turbulence parameter estimation because the EVMs are likely to be quasi-two-dimensional vortex structures that are embedded within the three-dimensional turbulence on the inside edge of the eyewall. This study is a first attempt at estimating the characteristics of turbulent flow in the low-level troposphere of an intense eyewall using in situ aircraft observations. The authors believe that the results can offer useful guidance in numerical weather prediction efforts aimed at improving the forecast of hurricane intensity. Because of the small sample size analyzed in this study, further analyses of the turbulent characteristics in the high-wind region of hurricanes are imperative.

Momentum transport and dissipative heating are investigated using the high-resolution (10 Hz) wind data collected by Florida Coastal Monitoring Program portable weather stations in the surface layer of three landfalling hurricanes. The momentum flux is calculated using the eddy correlation method. The drag coefficient is determined from the momentum flux and surface wind speed. The values of the momentum flux and drag coefficient are found to be generally larger than those observed over the ocean at similar wind speeds up to near hurricane strength. The rate of dissipation is determined from the wind velocity spectra. The dissipative heating is estimated using two different methods: (1) integrating the rate of dissipation in the surface layer; and (2) multiplying the drag coefficient by the cubic of the surface wind speed. It is found that the second method, which has been widely used in previous theoretical and numerical studies, significantly overestimates the magnitude of dissipative heating. This finding is consistent with a recent study on estimation of the dissipative heating over the ocean using in situ aircraft observations. This study is a first attempt at estimating the magnitude of dissipative heating in landfalling hurricanes using in situ observations. The results are believed to offer useful guidance in numerical weather prediction efforts aimed at improving the forecast of hurricane intensity.

In this study, data from 794 GPS dropsondes deployed by research aircraft in 13 hurricanes are analyzed to study the characteristic height scales of the hurricane boundary layer. The height scales are defined in a variety of ways: the height of the maximum total wind speed, the inflow layer depth, and the mixed layer depth. The height of the maximum wind speed and the inflow layer depth are referred to as the dynamical boundary layer heights, while the mixed layer depth is referred to as the thermodynamical boundary layer height. The data analyses show that there is a clear separation of the thermodynamical and dynamical boundary layer heights. Consistent with previous studies on the boundary layer structure in individual storms, the dynamical boundary layer height is found to decrease with decreasing radius to the storm center. The thermodynamic boundary layer height, which is much shallower than the dynamical boundary layer height, is also found to decrease with decreasing radius to the storm center. The results also suggest that using the traditional critical Richardson number method to determine the boundary layer height may not accurately reproduce the height scale of the hurricane boundary layer. These different height scales reveal the complexity of the hurricane boundary layer structure that should be captured in hurricane model simulations.

Using the hurricane weather research and forecasting experimental modeling system (HWRFx), researchers examined the impact of increased model resolution on system performance in forecasting a select sample of tropical cyclones from the 2005 and 2007 hurricane seasons.

In 1997, the National Hurricane Center and the Hurricane Research Division began operational synoptic surveillance missions with the Gulfstream IV-SP jet aircraft to improve the numerical guidance for hurricanes that threaten the continental United States, Puerto Rico, the U. S. Virgin Islands, and Hawaii. During the first ten years, 176 such missions were conducted. Global Positioning System dropwindsondes were released from the aircraft at 150-200 km intervals along the flight track in the environment of each tropical cyclone to obtain wind, temperature, and humidity profiles from flight level (about 150 hPa) to the surface. The observations were processed and formatted aboard the aircraft and sent to the National Centers for Environmental Prediction and the Global Telecommunications System to be ingested into the Global Forecast System, which serves as initial and boundary conditions for regional numerical models that also forecast tropical cyclone track and intensity. The results of an observing system experiment using these data are presented.

Nine different types of aircraft are currently in use to observe tropical cyclones and their environments for operations and research. The following is a description of those aircraft, their instrumentation, and the field programs with which they have been involved.

The quality of convective-scale ensemble forecasts, initialized from analysis ensembles obtained through the assimilation of radar observations using an ensemble Kalman filter (EnKF), is investigated for cases whose behaviors span supercellular, linear, and multicellular organization. This work is the companion to Part I, which focused on the quality of analyses during the 60-min analysis period. Here, the focus is on 30-min ensemble forecasts initialized at the end of that period. As in Part I, the Weather Research and Forecasting (WRF) model is employed as a simplified cloud model at 2-km horizontal grid spacing. Various observation-space and state-space verification metrics, computed both for ensemble means and individual ensemble members, are employed to assess the quality of ensemble forecasts comparatively across cases. While the cases exhibit noticeable differences in predictability, the forecast skill in each case, as measured by various metrics, decays on a time scale of tens of minutes. The ensemble spread also increases rapidly but significant outlier members or clustering among members are not encountered. Forecast quality is seen to be influenced to varying degrees by the respective initial soundings. While radar data assimilation is able to partially mitigate some of the negative effects in some situations, the supercell case, in particular, remains difficult to predict even after 60 min of data assimilation.

Airborne Doppler radar observations from the recent Tropical Cyclone Structure 2008 (TCS08) field campaign in the western North Pacific reveal the presence of deep, buoyant and vortical convective features within a vertically-sheared, westward-moving pre-depression disturbance that later developed into Typhoon Hagupit. On two consecutive days, the observations document tilted, vertically coherent precipitation, vorticity, and updraft structures in response to the complex shearing flows impinging on and occurring within the disturbance near 18 north latitude. The observations and analyses herein suggest that the low-level circulation of the pre-depression disturbance was enhanced by the coupling of the low-level vorticity and convergence in these deep convective structures on the meso-gamma scale, consistent with recent idealized studies using cloud-representing numerical weather prediction models. Further examination of these new observations is needed to quantify the relative role of these vortical convection features in the tropical cyclone spin up process.

Several hypotheses have been put forward for the mechanisms of generation of surface circulation associated with tropical cyclones. This paper examines high-resolution simulations of Tropical Storm Gert (2005), which formed in the Gulf of Mexico during NASAs Tropical Cloud Systems and Processes Experiment, to investigate the development of low-level circulation and its relationship to the precipitation evolution. Two simulations are examined: one that better matches available observations but underpredicts the storms minimum sea level pressure and a second one that somewhat overintensifies the storm but provides a set of simulations that encapsulates the overall genesis and development characteristics of the observed storm. The roles of convective and stratiform precipitation processes within the mesoscale precipitation systems that formed Gert are discussed. During 21-25 July, two episodes of convective system development occurred. In each, precipitation system evolution was characterized by intense and deep convective upward motions followed by increasing stratiform-type vertical motions (upper-level ascent, low-level descent). Potential vorticity (PV) in convective regions was strongest at low levels while stratiform-region PV was strongest at midlevels, suggesting that convective processes acted to spin up lower levels prior to the spinup of middle levels by stratiform processes. Intense vortical hot towers (VHTs) were prominent features of the low-level cyclonic vorticity field. The most prominent PV anomalies persisted more than 6 h and were often associated with localized minima in the sea level pressure field. A gradual aggregation of the cyclonic PV occurred as existing VHTs near the center continually merged with new VHTs, gradually increasing the mean vorticity near the center. Nearly concurrently with this VHT-induced development, stratiform precipitation processes strongly enhanced the mean inflow and convergence at middle levels, rapidly increasing the midlevel vorticity. However, the stratiform vertical motion profile is such that while it increases midlevel vorticity, it decreases vorticity near the surface as a result of low-level divergence. Consequently, the results suggest that while stratiform precipitation regions may significantly increase cyclonic circulation at midlevels, convective vortex enhancement at low to mid levels is likely necessary for genesis.

A coupled system of wind, wind wave, and coastal circulation models has been implemented for southern Louisiana and Mississippi to simulate riverine flows, tides, wind waves, and hurricane storm surge in the region. The system combines the NOAA Hurricane Research Division Wind Analysis System (H*WIND) and the Interactive Objective Kinematic Analysis (IOKA) kinematic wind analyses, the Wave Model (WAM) offshore and Steady-State Irregular Wave (STWAVE) nearshore wind wave models, and the Advanced Circulation (ADCIRC) basin to channel-scale unstructured grid circulation model. The system emphasizes a high-resolution (down to 50 m) representation of the geometry, bathymetry, and topography; nonlinear coupling of all processes including wind wave radiation stress-induced set up; and objective specification of frictional parameters based on land-cover databases and commonly used parameters. Riverine flows and tides are validated for no storm conditions, while winds, wind waves, hydrographs, and high water marks are validated for Hurricanes Katrina and Rita.

Haywood et al. (2004) showed that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space-based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below-aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol-induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 µm) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS-retrieved cloud optical thickness and effective radius can reach values of 10 and 10 µm, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

A set of multiscale, nested, idealized numerical simulations of mesoscale convective systems (MCSs) and mesoscale convective vortices (MCVs) was conducted. The purpose of these simulations was to investigate the dependence of MCV development and evolution on background conditions and to explore the relationship between MCVs and larger, moist baroclinic cyclones. In all experiments, no mesoscale convective system (MCS) developed until a larger-scale, moist baroclinic system with surface pressure amplitude of at least 2 hPa was present. The convective system then enhanced the development of the moist baroclinic system by its diabatic production of eddy available potential energy (APE), which led to the enhanced baroclinic conversion of basic-state APE to eddy APE. The most rapid potential vorticity (PV) development occurred in and just behind the leading convective line. The entire system grew upscale with time as the newly created PV rotated cyclonically around a common center as the leading convective line continued to expand outward. Ten hours after the initiation of deep moist convection, the simulated MCV radii, heights of maximum winds, tangential velocity, and shear corresponded reasonably well to their counterparts in BAMEX. The increasing strength of the simulated MCVs with respect to larger values of background CAPE and shear supports the hypothesis that as long as convection is present, CAPE and shear both add to the strength of the MCV.

Hurricanes Katrina and Rita were powerful storms that impacted southern Louisiana and Mississippi during the 2005 hurricane season. In Part I, the authors describe and validate a high-resolution coupled riverine flow, tide, wind, wave, and storm surge model for this region. Herein, the model is used to examine the evolution of these hurricanes in more detail. Synoptic histories show how storm tracks, winds, and waves interacted with the topography, the protruding Mississippi River delta, eastwest shorelines, manmade structures, and low-lying marshes to develop and propagate storm surge. Perturbations of the model, in which the waves are not included, show the proportional importance of the wave radiation stress gradient induced setup.

A tropical disturbance made landfall near Morehead City, North Carolina, on 27 June 2006. Surface observations, Air Force reconnaissance, and Doppler velocity data suggest that the disturbance had a closed surface circulation at landfall, with maximum 1-min surface winds >18 m s^-1, the threshold of tropical storm strength. A cyclostrophic wind calculation using Doppler velocity data and surface observations indicates that the circulation of the disturbance likely caused the tropical storm force winds observed, rather than an environmental pressure gradient or short-lived convective process. Doppler velocity cross sections of the disturbance further suggest that the disturbance was warm core, and an analysis of the disturbances environment reveals that latent heat of condensation was likely a large source of energy for the disturbance, though there was some baroclinic forcing. These observations and analyses make a compelling case for the upgrade of the disturbance to a tropical storm in the best-track database.

As an environmental phenomenon, hurricanes cause significant property damage and loss of life in coastal areas almost every year. Although a number of commercial loss projection models have been developed to predict the property losses, only a handful of studies are available in the public domain to predict damage for hurricane prone areas. The state of Florida has developed an open, public model for the purpose of probabilistic assessment of risk to insured residential property associated with wind damage from hurricanes. The model comprises three components; viz. the atmospheric science component, the engineering component and the actuarial science component. The atmospheric component includes modeling the track and intensity life cycle of each simulated hurricane within the Florida threat area. Based on historical hurricane statistics, thousands of storms are simulated allowing determination of the wind risk for all residential zip code locations in Florida. The wind risk information is then provided to the engineering and actuarial components to model damage and average annual loss, respectively. The actuarial team finds the county-wise loss and the total loss for the entire state of Florida. The computer team then compiles all information from atmospheric science, engineering and actuarial components, processes all hurricane related data and completes the project. The model was submitted to the Florida Commission on Hurricane Loss Projection Methodology for approval and went through a rigorous review and was revised as per the suggestions of the commission. The final model was approved for use by the insurance companies in Florida by the commission. At every stage of the process, statistical procedures were used to model various parameters and validate the model. This paper presents a brief summary of the main components of the model (meteorology, vulnerability and actuarial) and then focuses on the statistical validation of the same.

Hurricanes are fueled by evaporation and convection from the ocean and they lose energy through the frictional drag of the atmosphere on the ocean surface. The relative rates of these processes have been thought to provide a limit on the maximum potential hurricane intensity. Here we report laboratory observations of these transfers for scaled winds equivalent to a strong Category 1 hurricane (38 ms^-1). We show that the transfer coefficient ratio holds closely to a level of ~0.5 even in the highest observed winds, where previous studies have suggested there is a distinct regime change at the air-sea interface. This value is well below the expected threshold value for intense hurricanes of 0.75. Recent three-dimensional model studies also find that the coefficient ratio can be much lower than 0.75, which suggests that other factors such as eyewall and/or vortex dynamics are responsible for the formation of very strong hurricanes.

The Lidar Atmospheric Sensing Experiment (LASE) on board the NASA DC-8 measured high-resolution profiles of water vapor and aerosols, and cloud distributions in 14 flights over the eastern North Atlantic during the NASA African Monsoon Multidisciplinary Analyses (NAMMA) field experiment. These measurements were used to study African easterly waves (AEWs), tropical cyclones (TCs), and the Saharan air layer (SAL). These LASE measurements represent the first simultaneous water vapor and aerosol lidar measurements to study the SAL and its interactions with AEWs and TCs. Three case studies were selected for detailed analysis: (i) a stratified SAL, with fine structure and layering (unlike a well-mixed SAL), (ii) a SAL with high relative humidity (RH), and (iii) an AEW surrounded by SAL dry air intrusions. Profile measurements of aerosol scattering ratios, aerosol extinction coefficients, aerosol optical thickness, water vapor mixing ratios, RH, and temperature are presented to illustrate their characteristics in the SAL, convection, and clear air regions. LASE extinction-to-backscatter ratios for the dust layers varied from 35 ± 5 to 45 ± 5 sr, well within the range of values determined by other lidar systems. LASE aerosol extinction and water vapor profiles are validated by comparison with onboard in situ aerosol measurements and GPS dropsonde water vapor soundings, respectively. An analysis of LASE data suggests that the SAL suppresses low-altitude convection. Midlevel convection associated with the AEW and transport are likely responsible for high water vapor content observed in the southern regions of the SAL on 20 August 2008. This interaction is responsible for the transfer of about 7 x 10¹⁵ J (or 8 x 10³ J m^-2) latent heat energy within a day to the SAL. Initial modeling studies that used LASE water vapor profiles show sensitivity to and improvements in model forecasts of an AEW.

A revised rapid intensity index (RII) is developed for the Atlantic and eastern North Pacific basins. The RII uses large-scale predictors from the Statistical Hurricane Intensity Prediction Scheme (SHIPS) to estimate the probability of rapid intensification (RI) over the succeeding 24 h utilizing linear discriminant analysis. Separate versions of the RII are developed for the 25-, 30-, and 35-kt RI thresholds, which represent the 90th (88th), 94th (92nd), and 97th (94th) percentiles of 24-h over water intensity changes of tropical and subtropical cyclones in the Atlantic (eastern North Pacific) basins from 1989 to 2006, respectively. The revised RII became operational at the NHC prior to the 2008 hurricane season. The relative importance of the individual RI predictors is shown to differ between the two basins. Specifically, the previous 12-h intensity change, upper-level divergence, and vertical shear have the highest weights for the Atlantic basin, while the previous 12-h intensity change, symmetry of inner-core convection, and the difference in a systems current and maximum potential intensity are weighted highest in the eastern North Pacific basin. A verification of independent forecasts from the 2006 and 2007 hurricane seasons shows that the probabilistic RII forecasts are generally skillful in both basins when compared to climatology. Moreover, when employed in a deterministic manner, the RII forecasts were superior to all other available operational intensity guidance in terms of the probability of detection (POD) and false alarm ratio (FAR). Specifically, the POD for the RII ranged from 15% to 59% (53% to 73%) while the FAR ranged from 71% to 85% (53% to 79%) in the Atlantic (eastern North Pacific) basins, respectively, for the three RI thresholds studied. Nevertheless, the modest POD and relatively high FAR of the RII and other intensity guidance demonstrate the difficulty of predicting RI, particularly in the Atlantic basin.

Hurricane turbulent kinetic energy (TKE) was computed using airborne Doppler measurements from the NOAA WP-3D tail radars and TKE data were retrieved for a variety of storms at different stages of their lifecycle. The geometry of the radar analysis coupled with the relatively small beam resolution at ranges <8 km allowed for the estimation of sub-kilometer turbulent processes. Two dimensional profiles of TKE were constructed and revealed that the strongest turbulence was in general located in convective regions such as the eyewall with magnitude often exceeding 15 m² s^-2, and in the boundary layer with values of 5-10 m² s^-2 in the lowest km. A correlation analysis showed that the strong turbulence was in general associated with strong horizontal shear of vertical and radial wind components in the eyewall and strong vertical shear of horizontal wind in the boundary layer. Mean vertical profiles of TKE decrease sharply above the hurricane boundary layer and level off at low magnitude for all regions outside the radius of maximum wind. The quality of the retrieval method was evaluated and showed very good agreement with TKE values directly calculated from the three-dimensional wind components of in-situ measurements. The method presented here provides a unique opportunity to assess hurricane turbulence throughout the storm, especially in high wind regions, and can be applied on extensive data sets of past and future airborne hurricane penetrations.

The characteristics of target locations of tropospheric wind and temperature identified by a modified version of the ensemble transform Kalman filter (ETKF), in order to reduce 0-7-day forecast errors over North America, are explored from the perspective of a field program planner. Twenty cases of potential high-impact weather over the continent were investigated, using a 145-member ensemble comprising perturbations from NCEP, ECMWF, and the Canadian Meteorological Centre (CMC). Multiple targets were found to exist in the midlatitude storm track. In half of the cases, distinctive targets could be traced upstream near Japan at lead times of 4-7 days. In these cases, the flow was predominantly zonal and a coherent Rossby wave packet was present over the northern Pacific Ocean. The targets at the longest lead times were often located within propagating areas of baroclinic energy conversion far upstream. As the lead time was reduced, these targets were found to diminish in importance, with downstream targets corresponding to a separate synoptic system gaining in prominence. This shift in optimal targets is sometimes consistent with the radiation of ageostrophic geopotential fluxes and transfer of eddy kinetic energy downstream, associated with downstream baroclinic development. Concurrently, multiple targets arise due to spurious long-distance correlations in the ETKF. The targets were least coherent in blocked flows, in which the ETKF is known to be least reliable. The effectiveness of targeting in the medium range requires evaluation, using data such as those collected during the winter phase of The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Field Campaign (T-PARC) in 2009.

Stimulated by recent developments in understanding tropical cyclones, we offer an evaluation of an analytical model that has been proposed to explain the rapid intensification of these storms. We articulate a number of concerns with this model, including the neglect of both the vertical momentum equation and the thermodynamic equation, and conclude that it falls a little short of achieving its stated aims.

Motivated by recent developments in tropical-cyclone dynamics, this paper re-examines a basic aspect of tropical-cyclone behavior, namely, the sensitivity of tropical-cyclone models to the surface drag coefficient. Previous theoretical and numerical studies of the sensitivity in axisymmetric models have found that the intensity decreases markedly with increasing drag coefficient. Here we present a series of three-dimensional convection-permitting numerical experiments in which the intensification rate and intensity of the vortex increase with increasing surface drag coefficient until a certain threshold value is attained and then decrease. In particular, tropical depression-strength vortices intensify to major hurricane intensity for values of CK/CD as small as 0.1, significantly smaller than the critical threshold value of about 0.75 for major hurricane development predicted by Emanuel using an axisymmetric balance model. Moreover, when the drag coefficient is set to zero, no system-scale intensification occurs, despite persistent sea-to-air fluxes of moisture that maintain deep convective activity. This result is opposite to that found in a prior axisymmetric study by Craig and Gray. The findings are interpreted using recent insights obtained on tropical-cyclone intensification, which highlight the intrinsically unbalanced dynamics of the tropical-cyclone boundary layer. The reasons for the differences from earlier axisymmetric studies and some potential ramifications of our findings are discussed. The relative insensitivity of the intensification rate and intensity found for drag coefficients typical of high wind speeds over the ocean calls into question the need for coupled ocean wave-atmospheric models to accurately forecast tropical-cyclone intensity.

This study explores the functional relationship between model physics parameters and model output variables for the purpose of (1) characterizing the sensitivity of the simulation output to the model formulation and (2) understanding model uncertainty so that it can be properly accounted for in a data assimilation framework. A Markov chain Monte Carlo algorithm is employed to examine how changes in cloud microphysical parameters map to changes in output precipitation, liquid and ice water path, and radiative fluxes for an idealized deep convective squall line. Exploration of the joint probability density function (PDF) of parameters and model output state variables reveals a complex relationship between parameters and model output th