1. A Novel Ocean Vector Winds Retrieval Technique for Tropical Cyclones Peth Laupattarakasem 1, Suleiman Alsweiss1, W. Linwood Jones 1, and Christopher C. Hennon 2 1 Central Florida Remote Sensing Laboratory University of Central Florida Orlando, Florida 32816 2 University of North Carolina Asheville Asheville, NC 28804 IGARSS 2011 Vancouver, Canada July 26, 2011

2. Outline SeaWinds OVW measurements in hurricanes Radar backscatter geophysical model function X-Winds OVW retrieval algorithm –wind direction retrieval –wind speed retrieval X-Wind Comparisons with H*Wind & QuikSCAT standard L2B OVW product

3. SeaWinds Hurricane Measurements Historically Ku-band scatterometers have under estimated hurricane wind speeds Issues –Inadequate spatial resolution (25 km IFOV) –Rain contamination (backscatter & attenuation) –Geophysical OVW retrieval algorithm Developed for global winds Not optimized for tropical cyclones

4. Extreme Winds Sigma-0 Geophys Model Function (XW-GMF) Special QuikSCAT GMF developed for hurricanes –Training dataset of 35 QScat hurricane overpasses –3-D GMF:  o = f(ws, relative wdir, atmos transmis) WS: one-minute sustained 10m wind speeds from NOAA HRD H*Wind surface wind analysis Relative wind direction  the difference between wind direction and the radar azimuth look Atmos transmissivity: inferred from simultaneous observations of QRad H-pol brightness temperatures

5. Hurricane Geophysical Model Function (GMF) H-pol  o, dB 30 m/s

6. GMF C 0 - Coeff Dependence on Wind Speed C 0, dB 10 20 40 60 Wind Speed, m/s

7. GMF Anisotropy with Wind Speed C 1, linear units C 2, linear units 10 20 40 60 Wind Speed, m/s 10 20 40 60 Wind Speed, m/s

8. XW-GMF Atmospheric Transmissivity Rain attenuation is corrected implicitly through use of the QRad H-pol brightness temperature T bh –GMF = f(ws, rel_wdir, T bh ) T bh 140 k 160 k 190 k

9. X-Winds OVW retrieval Algorithm Attributes –Assumes cyclonic wind direction rotation about TC center –Assumes rain effects are primarily absorptive Rain volume backscatter is neglected –Empirical 3-D XW-GMF accounts for backscatter saturation with wind speed & rain absorption –Uses sequential scalar wind direction and wind speed estimation Not traditional ocean vector wind “maximum likelihood estimation” retrieval

10. Scalar Wind Direction Estimation Relies on anisotropy of measured difference between forward and aft looking backscatter measurements  o meas = (  o fore –  o aft ) @ top-of-the-atmos Latitude Index Longitude Index  o - linear units Typical hurricane image

11. Wind Direction Modeling of  o  o anisotropy model for single radar azimuth look Taking the difference between fore & aft radar looks yields Wind direction solutions (aliases) are roots of Yields ambiguous wind direction solutions typically ~ 6 – 8

12. Wind Direction Alias Removal Wind Directions AmbiguitiesRetrieved Wind Direction Field Keep ambiguities within window ±30  from CCW spiral Multi-pass median filter and populate missing pixels through interpolation Use smoothed TC wind field for wind speed estimation

13. X-Winds Scalar Wind Speed Estimation Use smooth TC wind field as “estimated true” wind direction and calculate relative wind direction  = (radar az – “est-wind dir”)  Find 1-D wind speed solution for each “  o flavor”  (V- & H-pol, fore & aft direction) that satisfies this relationship

14. X-Winds Wind Speeds Retrievals Wind Speed (m/s) |(  o meas – GMF)| 4 σ 0 flavors HF HA VF VA

15. - L2B-12.5km OVW product - H*Wind surface wind analysis X-Winds OVW retrievals Results and Performance Evaluation

16. Hurricane Fabian Rev#21898 X-Winds H*Wind Analysis L2B-WS 12.5km

17. Hurricane Ivan Rev#27217 X-Winds H*Wind L2B-WS 12.5km

18. Wind Speeds Comparison (10 revs) X-Winds QSCAT L2B-12.5km Tb H-pol

19. Wind Speeds Comparison (10 revs) X-Winds QSCAT L2B-12.5km Tb H-pol

20. Wind Direction Comparison (10 revs) Tb H-pol X-Winds QSCAT L2B-12.5km Tb H-pol

21. Wind Direction Comparison (10 revs) Tb H-pol X-Winds QSCAT L2B-12.5km Tb H-pol

22. Conclusion A new OVW retrieval algorithm has been developed for SeaWinds –Specifically tailored for tropical and extra-tropical cyclones Performance evaluated using comparisons with H*Wind surface wind analysis and L2B-12.5km –Better agreement with H*Wind A new (11-year) SeaWinds TC OVW data set will be produced starting next year 2012