Hurricane Research Division
FY-2000 Publications
(October 1, 1999-September 30, 2000)
(names of HRD authors appear in capital letters)
	[1]	Atlas, D., C.W. Ulbrich, F.D. MARKS, R.A. BLACK, E. Amitai, P.T. WILLIS, and C.E. Samsury.  Partitioning tropical oceanic convective and stratiform rains by draft strength.  Journal of Geophysical Research, 105(D2):2259-2267 (2000).
The discrimination of convective from stratiform tropical oceanic rains by conventional radar-based textural methods is problematic because of the small size and modest horizontal reflectivity gradients of the oceanic convective cells.  In this work, the vertical air motion measured by an aircraft gust probe is used as a discriminator which is independent of the textural methods.  A threshold draft magnitude of .1 m s-1 separates the two rain types.  Simultaneous airborne in-situ observations of drop size distributions (DSD) made during the Tropical Ocean Global Atmosphere-Coupled Ocean Atmosphere Response Experiment (TOGA-COARE) were used to compute Z, R, and other integral parameters.  The data were quality controlled to minimize misclassifications.  The convective and stratiform rains, observed just below the melting level but adjusted to surface air density, are characterized by power law Z-R relations (Z = 129R1.38 [convective] and 224R1.28 [stratiform]).  However, at R < 10 mm h-1, the convective population is essentially coincident with the small-drop size, small-Z portion of the stratiform population.  Tokay and Short (1996) found a similar result when their algorithm did not separate the rain types unambiguously at R < 10 mm h-1.  The physical reasons for the wide variability of the drop size spectra and Z-R points in stratiform rain and their overlap with that of convective rain are proposed.  The subtle distinctions in the microphysical properties and the Z-R relations by rain type could not be found by Yuter and Houze using the same airborne DSD data set as that in this work and a radar-based textural classification algorithm.
	[2]	Bosart, L.F., C.S. Velden, W.E. Bracken, J. Molinari, and P.G. BLACK.  Environmental influences on the rapid intensification of Hurricane Opal (1995) over the Gulf of Mexico.  Monthly Weather Review, 128(2):322-352 (2000).
Hurricane Opal intensified rapidly and unexpectedly over the Gulf of Mexico between 1800 UTC 3 October 1995 and 1000 UTC 4 October 1995. During this period, the storm central pressure decreased from 963 to 916 hPa and sustained winds reached 68 m s-1. Analyses that include high-resolution GOES-8 water vapor winds and European Centre for Medium-Range Weather Forecasts (ECMWF) and National Centers for Environmental Prediction (NCEP) gridded data sets are employed to examine the rapid intensification phase of Opal.  Opal first reached tropical storm strength on 29-30 September 1995 as it interacted with a trough while situated over the Yucatan Peninsula. Opal deepened moderately (20 hPa) in the 24 h ending 1200 UTC 2 October as it achieved minimal hurricane strength and turned northeastward. The deepening occurred in conjunction with an environmental flow interaction as determined by an Eliassen balanced vortex outflow calculation.  As Opal accelerated toward the Gulf coast by 1200 UTC 3 October, it approached the equatorward jet-entrance region of a progressive synoptic-scale trough. The trough tail extended southwestward toward the lower Texas coast. As the poleward portion of the trough moved eastward, the equatorward end of the trough lagged behind, stretched meridionally, and partially fractured as it encountered a deformation region over the northwest Gulf. Enhanced outflow and increased divergence in the upper troposphere poleward of Opal was associated with the deformation zone and the partially fractured trough tail.  An analysis of the 300-200-hPa layer-averaged divergence and 6-h divergence change based on an analysis of the water vapor winds shows a significant increase in the magnitude and equatorward extension of the divergence core toward Opal that begins at 1200 UTC 3 October and is most apparent by 1800 UTC 3 October and 0000 UTC 4 October. This divergence increase is shown to precede convective growth in the eyewall, and the onset of rapid intensification and is attributed to a jet-trough-hurricane interaction in a low-shear environment. Calculations of balanced vortex outflow based on the ECMWF and NCEP gridded data sets confirms this interpretation.  A crucial finding of this work is that the jet-trough-hurricane interaction and explosive intensification of Opal begins near 0000 UTC 4 October when the storm is far from its maximum potential intensity (MPI), and the 850-200-hPa shear within 500 km of the center is weak (2-3 m s-1). In this first stage of rapid intensification, the winds increase by almost 15 m s-1 to 52 m s-1 prior to the storm reaching an oceanic warm-core eddy. The second stage of rapid intensification occurs between 0600 and 1000 UTC 4 October when Opal is over the warm-core eddy and sustained winds increase to 68 m s-1. During this second stage, conditions are still favorable for a jet-trough-hurricane interaction as demonstrated by the balanced vortex outflow calculation.  Opal weakens rapidly after 1200 UTC 4 October when the storm is near its MPI, the shear is increasing, and the eye is leaving the warm-core eddy. This weakening occurs as Opal moves closer to the trough. It is suggested that an important factor in determining whether a storm-trough interaction is favorable or unfavorable for intensification is how far a storm is from its MPI.  The results suggest that a favorable storm-trough interaction (“good trough”) can occur when a storm is far from its MPI.  It is suggested that although the ECMWF (and to a lesser extent NCEP) analyses reveal the trough-jet-hurricane interaction through the balanced vortex outflow calculation, that the failure of the same models to predict the rapid intensification of Opal can be attributed to the inability of the model to resolve the eye and internal storm structure and the associated influence of the trough-jet-hurricane interaction on the diabatically driven storm secondary circulation. The analyses also indicate that the high spatial and temporal resolution of the GOES-8 water vapor winds reveal important mesoscale details of the trough-jet-hurricane interaction that would otherwise be hidden.
	[3]	CIONE, J.J., P.G. BLACK, and S.H. HOUSTON.  Surface observations in the hurricane environment.  Monthly Weather Review, 128(5):1550-1561 (2000).
Composite analyses of marine surface observations from 37 hurricanes between 1975 and 1998 show that the difference between the sea surface temperature and the surface air temperature significantly increases just outside the hurricane inner core.  This increase in the sea-air contrast is primarily due to a reduction in surface air temperature and is more likely to occur when sea temperatures are at least 27EC. Results show that 90% of the observed cooling occurs 3.25E-1.25E latitude from the hurricane center, well outside the region of strongest surface winds. Since surface pressure only decreases 3 mb over this interval, the 2EC drop in air temperature is not a result of adiabatic expansion.  For the subset of observations that contained moisture measurements, surface specific humidity decreased 1.2 g kg-1 4.5E-1.75E latitude from the storm center. This finding suggests that the observed reduction in surface air temperature is not simply a result of near-surface evaporation from sea spray or precipitation. An alternate explanation may be that outside the hurricane inner core unsaturated convective downdrafts act to dry and evaporatively cool the near-surface environment.  Between 3.25E and 1.25E radius, composite analyses show that low-level inflow is not isothermal, surface moisture is not constant, and the near-surface environment is not in thermodynamic equilibrium with the sea. Calculations based on these observations show that 2e decreases between 4.0E and 1.25E radius and then quickly rises near the inner core as surface pressures fall and specific humidity increases. Surface fluxes of heat and moisture are also observed to significantly increase near the inner core. The largest increase in surface sensible heat flux occurs radially inward of 1.5E, where surface winds are strong and sea-air temperature contrasts are greatest. As a result, the average Bowen ratio is 0.20-0.5E radius from the composite storm center. This increase in sensible heat flux (in conjunction with near-saturated conditions at low to midlevels) may help explain why average surface air temperatures inside 1.25E radius remain relatively constant, despite the potential for additional cooling from evaporation and adiabatic expansion within the high wind inner core.
	[4]	HOUSTON, S.H., W.A. Shaffer, M.D. POWELL, and J. Chen.  Comparisons of HRD and SLOSH surface wind fields in hurricanes: Implications for storm surge modeling.  Weather and Forecasting, 14(5):671-686 (1999).
Surface wind observations analyzed by the Hurricane Research Division (HRD) were compared to those computed by the parametric wind model used in the National Weather Service Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model’s storm surge computations for seven cases in five recent hurricanes. In six cases, the differences between the SLOSH and HRD surface peak wind speeds were 6% or less, but in one case (Hurricane Emily of 1993) the SLOSH computed peak wind speeds were 15% less than the HRD. In all seven cases, statistics for the modeled and analyzed wind fields showed that for the region of strongest winds, the mean SLOSH wind speed was 14% greater than that of the HRD and the mean inflow angle for SLOSH was 19E less than that of the HRD. The radii beyond the region of strongest winds in the seven cases had mean wind speed and inflow angle differences that were very small. The SLOSH computed peak storm surges usually compared closely to the observed values of storm surge in the region of the maximum wind speeds, except Hurricane Emily where SLOSH underestimated the peak surge. HRD’s observation-based wind fields were input to SLOSH for storm surge hindcasts of Hurricanes Emily and Opal (1995).  In Opal, the HRD input produced nearly the same computed storm surges as those computed from the SLOSH parametric wind model, and the calculated surge was insensitive to perturbations in the HRD wind field. For Emily, observation-based winds produced a computed storm surge that was closer to the peak observed surge, confirming that the computed surge in Pamlico Sound was sensitive to atmospheric forcing. Using real-time, observation-based winds in SLOSH would likely improve storm surge computations in landfalling hurricanes affected by synoptic and mesoscale factors that are not accounted for in parametric models (e.g., a strongly sheared environment, convective asymmetries, and stably stratified boundary layers).  An accurate diagnosis of storm surge flooding, based on the actual track and wind fields, could be supplied to emergency management agencies, government officials, and utilities to help with damage assessment and recovery efforts.
	[5]	Jacob, S.D., L.K. Shay, A.J. Mariano, and P.G. BLACK.  The 3D oceanic mixed layer response to Hurricane Gilbert.  Journal of Physical Oceanography, 30(6):1407-1429 (2000).
Upper-ocean heat and mass budgets are examined from three snapshots of data acquired during and after the passage of Hurricane Gilbert in the western Gulf of Mexico. Measurements prior to storm passage indicated a warm core eddy in the region with velocities of O(1) m s-1. Based upon conservation of heat and mass, the three-dimensional mixed layer processes are quantified from the data. During and subsequent to hurricane passage, horizontal advection due to geostrophic velocities is significant in the eddy regime, suggesting that prestorm oceanic variability is important when background flows have the same magnitude as the mixed layer current response. Storm-induced near-inertial currents lead to large vertical advection magnitudes as they diverge from and converge toward the storm track. Surface fluxes, estimated by reducing flight-level winds to 10 m, indicate a maximum wind stress of 4.2 N m-2 and a heat flux of 1200 W m-2 in the directly forced region. The upward heat flux after the passage of the storm has a maximum of 200 W m-2 corresponding to a less than 7 m s-1 wind speed.  Entrainment mixing across the mixed layer base is estimated using three bulk entrainment closure schemes that differ in their physical basis of parameterization. Entrainment remains the dominant mechanism in controlling the heat and mass budgets irrespective of the scheme. Depending on the magnitudes of friction velocity, surface fluxes and/or shear across the mixed layer base, the pattern and location of maximum entrainment rates differ in the directly forced region. While the general area of maximum entrainment is in the right-rear quadrant of the storm, the shear-induced entrainment scheme predicts a narrow region of cooling compared to the stress-induced mixing scheme and observed SST decreases. After storm passage, the maximum contribution to the mixed layer dynamics is associated with shear-induced entrainment mixing forced by near-inertial motions up to the third day as indicated by bulk Richardson numbers that remained below criticality. Thus, entrainment based on a combination of surface fluxes, friction velocity, and shear across the entrainment zone may be more relevant for three-dimensional ocean response studies.
	[6]	Katsaros, K.B., P. Vachon, P.G. BLACK, P.P. DODGE, and E.W. UHLHORN. Wind fields from SAR: Could they improve our understanding of storm dynamics? John Hopkins APL Technical Digest, 21(1):86-93 (2000).
Four hurricane images obtained by RADARSAT are examined for what they reveal about the storms. Features seen include strong variations in backscatter from the surface in and around convective cells associated with rain cells and rainbands, coupled with increased backscatter in regions of high wind outflow.  Long linear features of scale 3-6 km are observed in three of the four hurricanes, probably from secondary circulations in the atmospheric boundary layer (roll vortices). They occur between convective rainbands, where the descending motion could produce a well-defined boundary layer.  Although the origins of and the mechanisms producing the features are still not clear, the high resolution, wide-swath coverage modes of synthetic aperture radar provide new observations and present important questions for further research.
	[7]	LANDSEA, C.W.  Climate variability of tropical cyclones: Past, present, and future.  In Storms (Volume 1), R.A. Peilke, Sr. and R.A. Peikle, Jr. (eds.). Routledge, New York (ISBN 041517239X), 220-241 (2000).
No abstract.
	[8]	LANDSEA, C.W., and J.A. Knaff.  How much skill was there in forecasting the very strong 1997-1998 El Niño?  Bulletin of the American Meteorological Society, 81(9):2107-2120 (2000).
The very strong 1997-1998 El Niño was the first major event in which numerous forecasting groups participated in its real-time prediction. A previously developed simple statistical tool, the El Niño-Southern Oscillation Climatology and Persistence (ENSO-CLIPER) model, is utilized as a baseline for determination of skill in forecasting this event. Twelve statistical and dynamical models were available in real time for evaluation. Some of the models were able to outperform ENSO-CLIPER in predicting either the onset or the decay of the 1997-1998 El Niño, but none were successful at both for a medium-range two season (6-8 months) lead time. There were no models, including ENSO-CLIPER, able to anticipate even one-half of the actual amplitude of the El Niño's peak at medium-range (6-11 months) lead. In addition, none of the models showed skill (i.e., lower root-mean-square error than ENSO-CLIPER) at the zero season (0-2 months) through the two season (6-8 months) lead times.  No dynamical model and only two of the statistical models (the canonical correlation analysis [CCA] and the constructed analog [ANALOG]) outperformed ENSO-CLIPER by more than 5% of the root-mean-square error at the three season (9-11 months) and four season (12-14 months) lead time. El Niño impacts were correctly anticipated by national meteorological centers one-half year in advance, because of the tendency for El Niño events to persist into and peak during the boreal winter. Despite this, the zero to two season (0-8 month) forecasts of the El Niño event itself were no better than ENSO-CLIPER and were, in that sense, not skillful, a conclusion that remains unclear to the general meteorological and oceanographic communities.
	[9]	Lee, W.-C., and F.D. MARKS.  Tropical cyclone kinematic structure retrieved from single Doppler radar observations, Part II: The GBVTD-simplex center finding algorithm.  Monthly Weather Review, 128(6):1925-1936 (2000).
This paper is the second of a series and focuses on developing an algorithm to objectively identify tropical cyclone (TC) vorticity centers using single-Doppler radar data. The first paper dealt with the formulation of a single-Doppler radar TC wind retrieval technique, the ground-based velocity-track-display (GBVTD), and the results are verified using analytical TCs. It has been acknowledged that the quality of the GBVTD-retrieved TC circulation strongly depends on accurately knowing its center position. However, existing single-Doppler radar center finding algorithms are limited to estimate centers for axisymmetric TCs.  The proposed algorithm uses a simplex method to objectively estimate the TC vorticity center by maximizing GBVTD-retrieved mean tangential wind.  When tested with a number of axisymmetric and asymmetric analytical TCs, the accuracy of the TC centers estimated by the GBVTD-simplex algorithm is .340 m from the true center. When adding 5 m s-1 random noise to the Doppler velocities, the accuracy of the TC centers is nearly unchanged at 350 m. When applying the GBVTD-simplex algorithm to Typhoon Alex (1987), the estimated uncertainty varies between 0.1 and 2 km. When the overall velocity gradient is weak, the uncertainties in the retrieved TC centers are usually large. The GBVTD-simplex algorithm sometimes has problems finding a solution when a large sector of Doppler radar data is missing in conjunction with weak velocity gradients.  The GBVTD-simplex algorithm significantly reduces the uncertainties in estimating TC center position compared with existing methods and improves the quality of the GBVTD-retrieved TC circulation. The GBVTD-simplex algorithm is computationally efficient and can be easily adapted for real-time applications.
	[10]	Pielke, R.A., C.W. LANDSEA, R.T. Musulin, and M. Downton.  Evaluation of catastrophe models using a normalized historical record: Why it is needed and how to do it.  Journal of Risk and Insurance, 18:177-194 (1999).
No abstract.
	[11]	POWELL, M.D.  Tropical cyclones during and after landfall.  In Storms (Volume 1), R. Peilke, Sr. and R. Peikle, Jr. (eds.). Routledge, New York (ISBN 041517239X), 196-219 (2000).
No abstract.
	[12]	REASOR, P.D., M.T. Montgomery, F.D. MARKS, and J.C. GAMACHE.  Low-wavenumber structure and evolution of the hurricane inner core observed by airborne dual-Doppler radar.  Monthly Weather Review, 128(6):1653-1680 (2000).
The asymmetric dynamics of the hurricane inner-core region is examined through a novel analysis of high temporal resolution, three-dimensional wind fields derived from airborne dual-Doppler radar. Seven consecutive composites of Hurricane Olivia’s (1994) wind field with 30-min time resolution depict a weakening storm undergoing substantial structural changes. The symmetric and asymmetric mechanisms involved in this transformation are considered separately.  To zeroth order the weakening of the primary circulation is consistent with the axisymmetric vortex spindown theory of Eliassen and Lystad for a neutrally-stratified atmosphere. Vertical shear, however, increased dramatically during the observation period, leading to a strong projection of the convection onto an azimuthal wavenumber 1 pattern oriented along the maximum vertical shear vector. Recent theoretical ideas elucidating the dynamics of vortices in vertical shear are used to help explain this asymmetry.  The role of asymmetric vorticity dynamics in explaining some of the physics of hurricane intensity change motivates a special focus on Olivia’s vorticity structure. It is found that an azimuthal wavenumber 2 feature dominates the asymmetry in relative vorticity below 3-km height. The characteristics of this asymmetry deduced from reflectivity and wind composites during a  portion of the observation period show some consistency with a wavenumber 2 discrete vortex Rossby edge wave. Barotropic instability is suggested as a source for the wavenumber 2 asymmetry through a series of barotropic numerical simulations.  Trailing bands of vorticity with radial wavelengths of 5-10 km are observed in the inner core approximately 20 km from the storm center, and may be symmeterizing vortex Rossby waves. Elevated reflectivity bands with radial scales comparable to those of the vorticity bands, also near 20-25-km radius, may be associated with these vorticity features.
	[13]	ROGERS, R.F., J.M. Fritsch, and W.C. Lambert.  A simple technique for using radar data in the dynamic initialization of a mesoscale model.  Monthly Weather Review, 128(7):2560-2574 (2000).
A simple technique for using radar reflectivity to improve model initialization is presented.  Unlike previous techniques, the scheme described here does not infer rain rates and heating profiles from assumed relationships between remotely-sensed variables and precipitation rates.  Rather, the radar data are only used to tell the model when and where deep moist convection is occurring.  This information is then used to activate the model’s convective parameterization scheme in the grid elements where convection is observed.  This approach has the advantage that the convective precipitation rates and heating profiles generated by the convective parameterization are compatible with the local (grid element) environment.  The premise is that if convection is forced to develop when and where it is observed during a data assimilation period, convectively-forced modifications to the environment will be in the correct locations at the model initial forecast time and the resulting forecast will be more accurate.  Three experiments illustrating how the technique is applied in the simulation of deep convection in a warm-season environment are presented: a control run in which no radar data are assimilated, and two additional runs where radar data are assimilated for 12 h in one run and 24 h in the other.  The results indicate that assimilating radar data can improve a model’s description of the mesoscale environment during the pre-forecast time period, thereby resulting in an improved forecast of precipitation and the mesoscale environment.
	[14]	Shay, L.K., G.J. Goñi, and P.G. BLACK.  Effects of a warm oceanic feature on Hurricane Opal.  Monthly Weather Review, 128(5):1366-1383 (2000).
On 4 October 1995, Hurricane Opal deepened from 965 to 916 hPa in the Gulf of Mexico over a 14-h period upon encountering a warm core ring (WCR) in the ocean shed by the Loop Current during an upper-level atmospheric trough interaction. Based on historical hydrographic measurements placed within the context of a two-layer model and surface height anomalies (SHA) from the radar altimeter on the TOPEX mission, upper-layer thickness fields indicated the presence of two warm core rings during September and October 1995. As Hurricane Opal passed directly over one of these WCRs, the 1-min surface winds increased from 35 to more than 60 m s-1, and the radius of maximum wind decreased from 40 to 25 km. Pre-Opal SHAs in the WCR exceeded 30 cm where the estimated depth of the 20EC isotherm was located between 175 and 200 m. Subsequent to Opal’s passage, this depth decreased approximately 50 m, which suggests upwelling underneath the storm track due to Ekman divergence.  The maximum heat loss of approximately 24 Kcal cm-2 relative to depth of the 26EC isotherm was a factor of 6 times the threshold value required to sustain a hurricane. Since most of this loss occurred over a period of 14 h, the heat content loss of 24 Kcal cm-2 equates to approximately 20 kW m-2. Previous observational findings suggest that about 10-15% of upper-ocean cooling is due to surface heat fluxes. Estimated surface heat fluxes based upon heat content changes range from 2000 to 3000 W m-2 in accord with numerically simulated surface heat fluxes during Opal’s encounter with the WCR.  Composited AVHRR-derived SSTs indicated a 2-3EC cooling associated with vertical mixing in the along-track direction of Opal, except over the WCR where AVHRR-derived and buoy-derived SSTs decreased only by about 0.51EC. Thus, the WCR’s effect was to provide a regime of positive feedback to the hurricane rather than negative feedback induced by cooler waters due to upwelling and vertical mixing as observed over the Bay of Campeche and north of the WCR.