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Cross-Polarized SAR: A New Potential Technique for Hurricanes

This study explores the use of cross-polarized synthetic aperture radar (SAR) for wind speed retrievals in hurricanes. A polarization ratio model is developed to improve the accuracy of wind speed measurements. The model is compared to other SAR wind models and shows promising results. The study finds that the cross-polarized SAR technique is less sensitive to incidence angle and wind direction errors compared to traditional models. The potential for hurricane wind retrievals using cross-polarized SAR is discussed.

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Cross-Polarized SAR: A New Potential Technique for Hurricanes

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  1. Cross-Polarized SAR: A New Potential Technique for Hurricanes Will Perrie and Biao Zhang Bedford Institute of Oceanography Dartmouth, Nova Scotia, Canada

  2. SAR-wind models PR vs. incidence angle, from quad-polarization data.  Compared to other PR models … PR dependence onincidence angle We develop a polarization ratio model to improve wind speed retrievals…

  3. SAR PR ocean wind models Nonlinear Least Squares fit …. PR Model I only incidence angle dependence PR Model II with additional wind speed dependence

  4. Mouche et al #2 Our #1model Mouche et al #1 downwind Dataset Thompson et al Mouche et al #1 crosswind Johnsen et al Vachon&Dobson Elfouhaily Our #2 model PR PR from RADARSAT-2

  5. SAR winds from CMOD5.N and our model#I + R2 HH pol image Dataset 14.1 m/s 12.9 m/s 12.4 m/s 11.6 m/s 15.9 m/s 16.6 m/s Zhang, B., W. Perrie, and Y. He (2011), Wind speed from RADARSAT-2 quad-polarization images using a new polarization ratio model, J. Geophys. Res., doi:10.1029/2010JC006522. 17

  6. C-band models Co-Polarization Model:CMOD5.N HH VV HV 1:wind speed, wind direction, incidence angle. 2: NRCS_VV saturated under high winds. VH Cross-Polarization Ocean model: C-2PO U10 U10 Correlation coefficient for C-2PO = 0.91 1: only wind speed dependence. 2: NRCS_VH not saturated under high winds.

  7. R2 Quad-Polarization Ocean Backscatter Measurements Dataset NRCS_VV, NRCS_HH depend on incidence angle, wind direction NRCS_VV saturates U10 U10 NRCS_HV, NRCS_VH not sensitive to incidence angle, wind direction no NRCS_HV saturation C-2PO corr coeff = 0.91 U10 U10

  8. Hurricane wind-speed retrievals with C-2PO Hurricane Bertha – 12 July 2008

  9. Hurricane Ike – 10 Sept 2008

  10. Hurricane Bill – 22 Aug 2009

  11. Hurricane Danielle – 28 Aug 2010

  12. Hurricane Earlon Sep 02, 2010 at 22:59 UTC VH polarization VV polarization RADARSAT-2 dual-polarization SAR image

  13. Hurricane Earlon Sep 02, 2010 at 22:59 UTC Winds -buoy #41001 is 18.1 (m/s) C-2PO is 16.0 CMOD5.N is 17.4 H*Wind is 16.8 H*Wind (m/s) CMOD5.N(m/s) C-2PO model (m/s)

  14. Comparison of C-2PO and CMOD5. SAR wind retrievals eyewall? rain? gradients? Along track-SFMR (hr) time series SFMR-measured 10s rain rates (mm/hr) time series (hr)

  15. Hurricane Earl C-2PO CMOD5.N Comparisons of C-2PO and CMOD5.N SAR-retrieved winds U10 (Sep 02, 2010 at 22:59 UTC)with collocated H*Wind

  16. Hurricane Ike dual-polarization SAR image at 23:56 UTC on Sep 10, 2008 VV polarization VH polarization CMOD5.N + wind directions via H*Wind C-2PO model U10

  17. Hurricane Ike C-2PO CMOD5.N Comparisons of C-2PO and CMOD5.N SAR-retrieved winds U10 (23:56 UTC, on September 10, 2008) with collocated H*Wind CMOD5.N  bias of -4.89 m/s and RMS error of 6.51 m/s C-2PO  bias of -0.88 m/s and RMS error of 4.47 m/s

  18. Summary • C-2PO model presented • insensitive to wind direction, radar incidence angle • easy mapping of observed cross-pol NRCS to wind speed • avoids errors in wind speed retrievals that occur in CMOD5.N • in quad-pol data, C-2PO does not seem to saturate • potential for hurricane wind retrievals • dual-pol Earl:high wind comparisons R2 SAR – airborne SFMR • Earl: C-2PO bias= -0.89 m/s, RMSE= 3.23 m/s, CMOD5.N bias= -4.14 m/s, RMSE= 6.24 m/s. • Reasons for under-estimates: • CMOD5.N is saturated in high winds • co- and cross-polarized NRCS calibration error • CMOD5.N and C-2PO do not account for rain, high sea states, eye gradients, e.g. dampen the NRCS  biases in wind speeds • inaccurate wind directions for CMOD5.N.

  19. Some other sources… • Paul Hwang et al. TU2.T10.4 (11:20) Wind retrieval with cross-polarized SAR returns • Vladimir Zabeline et al. TH2.T02.2 RADARSAT Application in ocean wind measurements Hwang, P. A., B. Zhang, and W. Perrie, 2010: Depolarized radar return for breaking wave measurements and hurricane wind retrieval. Geophys. Res. Lett.,37, L01604, doi:10.1029/2009GL041780. Vachon, P.W. and J. Wolfe, (2010), C-band cross-polarization wind speed retrieval, IEEE Geosci. Remote Sens. Lett., 7, 456-459. Zhang, B., and W. Perrie (2010), C-band Quad-Polarization ocean backscatter measurements: A new polarization ratio model. SEASAR2010, January 25-29, Frascati, Italy. Zhang B., W. Perrie, and Y. He, 2011: Wind speed retrieval from RADARSAT-2 quad-polarization imagesusinga new polarization ratio model. J. Geophys. Res., 116, doi:10.1029/2010JC006522. Zhang, B., W. Perrie (2011), Cross-polarized synthetic aperture radar: a new measurement technique for Hurricanes, under review - Bulletin of the American Meteorological Society (BAMS).

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