High Quality Wind Retrievals for Hurricanes Using the SeaWinds Scatterometer W. Linwood Jones and Ian Adams Central Florida Remote Sensing Lab Univ. of Central FL

Presentation Outline Hurricane Wind Vector Retrieval Issues CFRSL Hurricane Retrieval Algorithm QRad Rain Rate Algorithm Isabel and Fabian Results Conclusion

Issues with L2B Wind Vector Retrieval for Extreme Wind Events Wind retrievals not tuned for high wind speeds  Geophysical Model Function developed for wind speeds < 20 m/s CFRSL Approach  Tropical Cyclone GMF tuned for retrieving high wind speeds  Blended UMASS aircraft scat measurements and NSCAT GMF

Issues with L2B Wind Vector Retrieval for Extreme Wind Events Egg spatial 25 km sampling is too coarse CFRSL Approach  Uses gridded “slice 12.5 Km sampling

25 km resolution using “eggs” 50 km 25 km Longitude Latitude

Range gated “slices” from “egg” 6 km 30 km 12.5 km 25 km

Issues with L2B Wind Vector Retrieval for Extreme Wind Events Rain has negative effects on wind measurements  Rain attenuation lowers retrieved wind speeds  Volume scattering increases retrieved wind speeds and alters directional signatures  Rain “splash” increases retrieved wind speeds and changes anisotropic ocean surface features  MUDDH performance in hurricanes is poor

Issues with L2B Wind Vector Retrieval for Extreme Wind Events Rain has negative effects on wind measurements CFRSL Approach  Simultaneous rain measurement using QRad  Rain attenuation and volume backscatter correction provided  Rain splash effect included in GMF  Rain Quality Flags Provided

CFRSL Hurricane Retrieval Algorithm “Slice” sigma-0’s for improved spatial resolution km Sigma-0 minimum eye location Wind speed retrieved from individual sigma-0 (assumed spiral wind directions) Rain inferred using QRad rain rate algorithm Sigma-0 corrections from atmospheric transmissivity and rain volume backscatter Flag pixels that correspond to high rain attenuation

QRad Algorithm Block Diagram Bin Slice Sig-0 Spiral Wind Direction Atmos. Atten and Backscatter Correction L2A Tb’s Hurricane Wind Speed QScat L1B sig-0 Locate Center QRad Rain Rate Retrieve Wind Speed Hurricane Wind Retrieval

Hurricane Eye Location Based upon Average of “4-flavor” Sigma-0’s 12.5 km sampling Longitude Latitude

QRad/SRad Rain Algorithm Look at noise channel of scatterometer  Subtract echo channel  Calibrate radiometric temperature vs. TMI Train brightness temperature/rain rate relationship via TMI Coincident with scatterometer measurement

QRad Integ. Rain Rate Product Improved CFRSL rain retrieval algorithm provides earth-gridded 50 km data product Instantaneous integrated rain rates > 2.4 km*mm/hr Resampled to 12.5 km wind vector grid

QRad – TRMM 2A12 Instantaneous Rain Rate QRad TMI Longitude Latitude Land

QRad – TRMM 3B42RT HQ Instantaneous Collocated Low Rain event QRad TMI

QRad – TRMM 3B42RT HQ Instantaneous Collocated Moderate Rain event QRadTMI

QRad – TRMM 3B42RT HQ Instantaneous Collocated High Rain Event QRadTMI

QRad (CFRSL) & TMI Integrated Rain Rates for Simultaneous Events TMI Integ. Rain Rate, km*mm/hr CFRSL Integ. Rain Rate, km*mm/hr

AMSR vs. SRad Path Attenuation, Horizontal Polarization 10 2 AMSR Attenuation SRad Attenuation

2003 Hurricane Results

HRD Wind Field, Time Interpolated CFRSL Wind Retrieval QRad Rain Rate (mm/hr) QuikSCAT Rev , Sept 13, :04 Z (m/sec) SSMI Rain Rate

HRD Wind Field, Time Interpolated (m/sec) SeaWinds Rev , Sept 15, :40 Z SRad Rain Rate (mm/hr) CFRSL Wind Retrieval SSMI Rain Rate

CFRSL Wind Retrieval SRad Rain Rate (mm/hr) HRD Wind Field, Time Interpolated (m/sec) QuikSCAT Rev , Sept 15, :52 Z SSMI Rain Rate

HRD Wind Field 01:30 Z SeaWinds Rev , Sept 16, :52 Z CFRSL Wind Retrieval SRad Rain Rate (mm/hr) (m/sec) SSMI Rain Rate

HRD Modeled Wind Speed (m/s) CFRSL Wind Speed (m/s) HRD Modeled Wind Speed (m/s) JPL Wind Speed (m/s) SeaWinds Rev , Sept 16, :52 Z JPL Wind FieldCFRSL Wind Retrieval

QuikSCAT vs. H* Wind Analysis

SeaWinds vs. HRD Model

CFRSL Algorithm Composite Wind Speeds

Conclusion Ready to test current algorithm in operational environment  Acceptable estimates of high rain rates inside storm conditions  Reasonable wind speed retrievals up to m/s Work must be done to improve model function and rain backscatter and attenuation estimates  Will utilize UMass IWRAP and SFMR data set  Have simultaneous AMSR and SRad for the 2003 hurricane season

Backup Slides

Error contribution of spiral direction