Real-time Doppler Radar

 Analyzing & Delivering Airborne Doppler Radar Data in “Real-Time”

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Background

Radar Systems Used

Tail Doppler Radar (TDR): The Tail Doppler Radar system is located at the back end of the aircraft. As the plane flies through a storm, the TDR continuously measures near-vertical cross-sections of precipitation and winds. By piecing together all of these cross-sections, scientists are then able to create a three-dimensional image of the storm. This three-dimensional “CAT scan” of the storm can show where the strongest winds are, how far the strong winds extend out from the storm center, and where the most intense rainfall is located. 

Photo of the Tail-Doppler Radar, located at the back of the P-3 aircraft. Photo Credit: AOML/ NOAA.

Photo of the Tail Doppler Radar, located at the back of the P-3 aircraft. Photo Credit: AOML/ NOAA.

Lower Fuselage (LF) Radar: The LF Radar system is located on the belly of the aircraft. It scans horizontally, much like an ordinary Doppler radar system would on the ground, and provides scientists with a high-time-resolution view of the swirling winds and precipitation near the altitude of the aircraft.

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The Quality-Control Process

In order to make the Tail Doppler Radar data useful in real-time, we developed an algorithm that automates the data quality-control process. In addition to effectively removing noise from the data, the algorithm properly interprets the Doppler wind measurements along the radar beam. Prior to the final development of this algorithm in 2005, the Tail Doppler Radar data had to be manually quality controlled by scientists, restricting its use primarily to research studies well after the hurricane season.

The automation of this quality-control process opens the doors to more timely research applications. It expands use of the Tail Doppler Radar data for all collaborators, and its use in real-time to enhance the guidance available to forecasters responsible for assessing the potential hurricane threats.

A scientist monitors the quality-control graphics while in the air. Photo Credit: AOML/ NOAA.

Scientists monitor the quality-control software while in the air. Photo Credit: AOML/ NOAA.

Next

Who We Are

A special thank you to our additional collaborators, including John Hill (OMAO/AOC), Christopher Mello (NHC), and Stephanie Stevenson (CIRA/NHC).

Paul D. Reasor
305.361.4530

| Paul D. Reasor

Principal Investigator

John F. Gamache
305.361.4437

| John F. Gamache

Co-Principal Investigator

Peter P. Dodge
305.361.4424

| Peter P. Dodge

Project Member
Frank Marks

Frank Marks
305.361.4321

| Frank D. Marks

Project Member

Joseph S. Griffin
305.361.4354

| Joseph S. Griffin

Project Member

Nancy F. Griffin
305.361.4353

| Nancy F. Griffin

Project Member

Jason A. Sippel
305.361.4368

| Jason A. Sippel

Project Member

What We Do

We gather airborne Doppler-radar wind and precipitation measurements from the P-3 and G-IV aircraft, quality control the data on the aircraft, and then deliver it to our National Weather Service partners in real-time. The quality-controlled data sent to the Environmental Modeling Center contributes to an accurate initialization of the Hurricane Weather Research and Forecasting model required for detailed forecasts of storm structure, intensity, and track.

The three-dimensional Tail Doppler Radar images of the storm and high-time-resolution Lower Fuselage Radar views of precipitation are sent directly to the National Hurricane Center and other local weather forecast offices. We also make these real-time radar products available to hurricane researchers within NOAA and across the globe to increase understanding of the processes at work within hurricanes. Read more about what we do on the HRD’s Blog.

Hurricane Hunters sit in the cockpit of the P3 (a specialized aircraft created to be a flying lab). Pilots approach the eye of a hurricane as shown through the front window. Photo Credit: NOAA.
Hurricane Hunters sit in the cockpit of the P3 (a specialized aircraft created to be a flying lab). Pilots approach the eye of a hurricane as shown through the front window. Photo Credit: NOAA.

Key Accomplishments

  • Operational assimilation of Doppler Radar data from NOAA P-3s

    September 2013

  • First assimilation of quality-controlled P-3 Doppler Radar data into experimental Hurricane Weather Research and Forecasting model

    October 2010

  • First successful transmission of superobs and assimilation into non-operational research model (WRF-ARW) in real-time

    August 2008

  • Hurricane Katrina: First real-time transmission to National Hurricane Center of real-time Doppler wind analyses done onboard the NOAA P-3 aircraft

    August 2005

  • Ground-based hurricane wind fields from single Doppler Radar

    September 1998

  • Vertically Scanning Doppler Radar

    August 1996

  • Transmission of airborne radar reflectivity images and Doppler wind fields from within the hurricane

    September 1993

Goals

Collect.

Since the late 1970s, AOML was significantly involved in developing and using the airborne radar systems on NOAA hurricane-hunter aircraft. We aim to advance the collection of radar data through evaluating new technology and refining hurricane sampling strategies.

Our recent focus is on collecting quality Doppler wind data, and are now working on making the most effective use of precipitation measurements from all radar systems. In 2019, we will begin assessing the research capabilities of the new Multi-Mode Lower Fuselage Radar system, including the potential for using horizontally-oriented Doppler wind measurements.

Deliver.

Our objective is to continue developing the algorithms that quality control and analyze radar data in real-time, as well as improving data delivery methods from the aircraft to the ground. We will work with our partners at the National Weather Service to provide timely radar products and aid them in the most effective use of the data.

Towards this end, we are working with the Environmental Modeling Center to determine whether assimilation of the analyzed winds produces greater positive impacts on forecasts than assimilation of the quality-controlled raw Doppler wind data. Additionally, this year will be the first time that the Tail Doppler Radar analyses are officially available in AWIPS-II for hurricane forecasters at the National Hurricane Center, Central Pacific Hurricane Center, and any other forecast offices. We also aim to develop real-time radar products that assist scientists during hurricane research missions.

Maintain.

AOML continues to oversee the maintenance of the airborne radar data and analysis repository. Although all the radar data and analyses from 2012 to the present are archived by the Science and Engineering Branch of the Aircraft Operations Center, we remain the sole points of contact for the use of radar data collected during hurricane missions.

We provide insight and context to the data sets in a manner that is useful to the science research community by integrating them with all of the additional data we collect. We continue to promote and facilitate the use of airborne radar data sets and real-time radar products in NOAA hurricane research and collaborations with researchers across the world.

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Current and Archived Hurricane Data

Satellite image of Hurricane Barry (2019).

2019 Hurricane Data

Missions, photos, radar, and satellite images from 2019.

2018 Hurricane Data

Missions, photos, radar, and satellite images from 2018.

Satellite image of Irma (2017). Photo Credit: AOML/ NOAA.

2017 Hurricane Data

Missions, photos, radar, and satellite images from 2017.

Hurricane Data Prior to 2017

Missions, photos, radar, and satellite images prior to 2017.

Impacts

Community Impact

Ultimately, by refining data analyses through quality-control methods, the National Hurricane Center can use the Hurricane Weather Research and Forecasting model to keep the community up-to-date and well informed during a hurricane. The protection of life and property is of the utmost importance during any extreme weather event, and AOML is able to serve the community by constantly collecting the most recent Doppler Radar data in real-time.

Scientific Impact

Over the past 30 years, improvements in Doppler radar technology have made substantial contributions to meteorologists’ key understanding of hurricane data. The development of this real-time, quality-controlled technology for Doppler data analysis is crucial to scientists and has made headway for new research projects aimed at improving the accuracy and quality of the data that these modernized instruments and tools collect.

Community Impact

Ultimately, by refining data analyses through quality-control methods, the National Hurricane Center can use the Hurricane Weather Research and Forecasting model to keep the community up-to-date and well informed during a hurricane. The protection of life and property is of the utmost importance during any extreme weather event, and AOML is able to serve the community by constantly collecting the most recent Doppler Radar data in real-time.

Scientific Impact

Over the past 30 years, improvements in Doppler radar technology have made substantial contributions to meteorologists’ key understanding of hurricane data. The development of this real-time, quality-controlled technology for Doppler data analysis is crucial to scientists and has made headway for new research projects aimed at improving the accuracy and quality of the data that these modernized instruments and tools collect.

Featured Publication

Publication Image: Wadler, J.B., R.F. Rogers, and P.D. Reasor. The relationship between spatial variations in the structure of convective bursts and tropical cyclone intensification using airborne Doppler radar. Monthly Weather Review, 146(3):761-780, doi:10.1175/MWR-D-17-0213.1 2018

The Relationship between Spatial Variations in the Structure of Convective Bursts and Tropical Cyclone Intensification as Determined by Airborne Doppler Radar

Abstract: The relationship between radial and azimuthal variations in the composite characteristics of convective bursts (CBs), that is, 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-yr 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 spinup. 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

Publication Image: Wadler, J.B., R.F. Rogers, and P.D. Reasor. The relationship between spatial variations in the structure of convective bursts and tropical cyclone intensification using airborne Doppler radar. Monthly Weather Review, 146(3):761-780, doi:10.1175/MWR-D-17-0213.1 2018
  • Publications & References

    Wadler, J.B., R.F. Rogers, and P.D. Reasor. The relationship between spatial variations in the structure of convective bursts and tropical cyclone intensification using airborne Doppler radar. Monthly Weather Review, 146(3):761-780, doi:10.1175/MWR-D-17-0213.1 2018

    Lorsolo, S., J. Gamache, and A. Aksoy. Evaluation of the Hurricane Research Division Doppler radar analysis software using synthetic data. Journal of Atmospheric and Oceanic Technology, 30(6):1055-1071, doi:10.1175/JTECH-D-12-00161.1 2013

    Reasor, P., R. Rogers, and S. Lorsolo. Environmental flow impacts on tropical cyclone structure diagnosed from airborne Doppler radar composites. Monthly Weather Review, 141(9):2949-2969,doi:10.1175/MWR-D-12-00334.1 2013

    Rogers, R., S. Lorsolo, P. Reasor, J. Gamache, and F.D. Marks, 2012: “Multiscale analysis of mature tropical cyclone structure from airborne Doppler composites,” Monthly Weather Review, 140 (1), P. 77-99 (January 2012)

    Lorsolo, S., F.D. Marks, J.F. Gamache, and J.A. Zhang, 2010: “Estimation and mapping of hurricane turbulent energy using airborne Doppler measurements.” Monthly Weather Review, 138(9)p.3656-3670 (September 2010)

    Nuissier, O., R.F. Rogers, and F.Roux, 2005: “A numerical simulation of Hurricane Bret on 22-23 August 1999 initialized with airborne Doppler radar and dropsonde data” Quar.Jour.Roy.Met.Soc., 131 (605) p.155-194 (Jan. 2005)

    Harasti,P.R., McAdie,C.J., Dodge, P.P., Lee, W-C, Tuttle, J., Murillo, S.T., Marks, F.D., 2004: “Real-Time Implementation of Single-Doppler Radar Analysis Methods for Tropical Cyclones: Algorithm Improvements and Use with WSR-88D Display Data,” Weather and Forecasting 19(2) 219-239 (February 2004)

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