Oceanography The Official Magazine of
The Oceanography Society
Volume 26 Issue 02

View Issue TOC
Volume 26, No. 2
Pages 46 - 57

OpenAccess

Tropical Cyclone Winds Retrieved from Synthetic Aperture Radar

By Jochen Horstmann , Christopher Wackerman, Silvia Falchetti , and Salvatore Maresca 
Jump to
Article Abstract Citation References Copyright & Usage
Article Abstract

This paper describes algorithms used to retrieve high-resolution wind fields in tropical cyclone conditions from synthetic aperture radar (SAR) data acquired at C-band with either co-polarization or cross-polarization. Wind directions are estimated from the orientation of wind-induced streaks visible in SAR images using a simple tropical cyclone flow field. Wind speeds are retrieved from the normalized radar cross section taking into account imaging geometry and SAR-retrieved wind direction using a geophysical model function. The algorithms are validated by comparing outputs to a set of SAR images acquired under tropical cyclone conditions. The simulated wind fields are compared to co-located results from the QuikSCAT scatterometer as well as to wind speeds measured by the Stepped Frequency Microwave Radiometer (SFMR) during reconnaissance flights through individual storms. Comparison of QuikSCAT winds to SAR co-polarization data shows that winds can be retrieved with a root mean square error of 17.6° for wind directions and 4.6 m s–1 for wind speeds. Comparison of SAR wind speeds to SFMR data result in a root mean square error of 5.7 m s–1 for co-polarization data and 3.8 m s–1 for cross-polarization data. SAR cross-polarization data are significantly better suited for SAR wind retrieval under tropical cyclone conditions at wind speeds above approximately 20 m s–1.

Citation

Horstmann, J., C. Wackerman, S. Falchetti, and S. Maresca. 2013. Tropical cyclone winds retrieved from synthetic aperture radar. Oceanography 26(2):46–57, https://doi.org/10.5670/oceanog.2013.30.

References
    Chelton, D.B., and M.H. Freilich. 2005. Scatterometer-based assessment of 10-m wind analyses from the operational ECMWF and NCEP numerical weather prediction models. Monthly Weather Review 133:409–429, https://doi.org/10.1175/MWR-2861.1.
  1. Dankert, H., and J. Horstmann. 2007. A marine radar wind sensor. Journal of Atmospheric and Oceanic Technology 24:1,629–1,642, https://doi.org/10.1175/JTECH2083.1.
  2. Gerling, T. 1986. Structure of the surface wind field from Seasat SAR. Journal of Geophysical Research 91:2,308–2,320, https://doi.org/​10.1029/JC091iC02p02308. 
  3. Hersbach, H. 2010. Comparison of C-Band scatterometer CMOD5.N equivalent neutral winds with ECMWF. Journal of Atmospheric and Oceanic Technology 27:721–736, https://doi.org/10.1175/2009JTECHO698.1.
  4. Horstmann, J., and W. Koch. 2005. Measurement of ocean surface winds using synthetic aperture radars. IEEE Journal of Oceanic Engineering 30:508–515, https://doi.org/​10.1109/JOE.2005.857514.
  5. Horstmann, J., W. Koch, S. Lehner, and R. Tonboe. 2000. Wind retrieval over the ocean using synthetic aperture radar with C-band HH polarization. IEEE Transactions on Geoscience and Remote Sensing 38:2,122–2,131, https://doi.org/10.1109/36.868871.
  6. Horstmann, J., W. Koch, S. Lehner, and R. Tonboe. 2002. Ocean winds from RADARSAT-1 ScanSAR. Canadian Journal of Remote Sensing 28:524–533, https://doi.org/10.5589/m02-043.
  7. Horstmann, J., D.R. Thompson, F. Monaldo, S. Iris, and H.C. Graber. 2005. Can synthetic aperture radars be used to estimate hurricane force winds? Geophysical Research Letters 32, L22801, https://doi.org/10.1029/2005GL023992. 
  8. Hwang, P.A., B. Zhang, and W. Perrie. 2010. Depolarized radar return for breaking wave measurements and hurricane wind retrieval. Geophysical Research Letters 37, L01604, https://doi.org/10.1029/2009GL041780. 
  9. Katsaros, K.B., P.W. Vachon, P.G. Black, P.P. Dodge, and E.W. Uhlhorn. 2000. Wind fields from SAR: Could they improve our understanding of storm dynamics? Johns Hopkins APL Technical Digest 21:86–93. 
  10. Katsaros, K.B., P.W. Vachon, W.T. Liu, and P.G. Black. 2002. Microwave remote sensing of tropical cyclones from space. Journal of Oceanography 58:137–151, https://doi.org/​10.1023/A:1015884903180. 
  11. Koch, W. 2004. Directional analysis of SAR images aiming at wind direction. IEEE Transactions on Geoscience and Remote Sensing 42:702–710, https://doi.org/10.1109/TGRS.2003.818811. 
  12. Lehner, S., J. Horstmann, W. Koch, and W. Rosenthal. 1998. Mesoscale wind measurements using recalibrated ERS SAR images. Journal of Geophysical Research 103(C4):7,847–7,856, https://doi.org/10.1029/97JC02726. 
  13. Monaldo, F., D. Thompson, R. Beal, W. Pichel, and P. Clemente-Colon. 2002. Comparison of SAR derived wind speed with model predictions and ocean buoy measurements. IEEE Transactions on Geoscience and Remote Sensing 39:2,587–2,600, https://doi.org/​10.1109/36.974994.
  14. Mouche, A., D. Hauser, J.-F. Daloze, and C. Guerinl. 2005. Dual-polarization measurements at C-band over the ocean: Results from airborne radar observations and comparisons with Envisat Asar data. IEEE Transactions on Geoscience and Remote Sensing 43:753–769, https://doi.org/10.1109/TGRS.2005.843951.
  15. Ochi, M.K. 2003. Hurricane-Generated Seas. Elsevier Ocean Engineering Book Series, vol. 8, Oxford, UK.
  16. Phillips, O.M. 1988. Radar returns from the sea surface: Bragg scattering and breaking waves. Journal of Physical Oceanography 18:1,065–1,074, https://doi.org/​10.1175/1520-0485(1988)018<1065:RRFTSS>2.0.CO;2.
  17. Reppucci, A., S. Lehner, J. Schulz-Stellenfleth, and S. Brusch. 2010. Tropical cyclone intensity estimated from wide-swath SAR images. IEEE Transactions on Geoscience and Remote Sensing 48:1,639–1,649, https://doi.org/​10.1109/TGRS.2009.2037143. 
  18. Shen, H., Y. He, and W. Perrie. 2009. Speed ambiguity in hurricane wind retrieval from SAR imagery. International Journal of Remote Sensing 30:2,827–2,836, https://doi.org/​10.1080/01431160802555879.
  19. Thompson, D., T. Elfouhaily, and B. Chapron. 1998. Polarization ratio for microwave backscattering from the ocean surface at low to moderate incidence angles. 1998. Pp. 1,671–1,673 in Proceedings of the International Geoscience and Remote Sensing Symposium, 1998, vol. 3. Seattle, WA, USA, https://doi.org/10.1109/IGARSS.1998.692411. 
  20. Touzi, R., P.W. Vachon, and J. Wolfe. 2010. Requirement on antenna cross-polarization isolation for the operational use of C-band SAR constellations in maritime surveillance. IEEE Geoscience and Remote Sensing Letters 7:861–865, https://doi.org/10.1109/LGRS.2010.2053835.
  21. Uhlhorn, E.W., P.G. Black, J.L. Franklin, M. Goodberlet, J. Carswell, and A.S. Goldstein. 2007. Hurricane surface wind measurements from an operational stepped frequency microwave radiometer. Monthly Weather Review 135:3,070–3,085, https://doi.org/​10.1175/MWR3454.1.
  22. Vachon, P., and F. Dobson. 2000. Wind retrieval from RADARSAT SAR images: Selection of a suitable C-band HH polarization wind retrieval model. Canadian Journal of Remote Sensing 26:306–313.
  23. Vachon, P., and J. Wolfe. 2011. C-band cross-polarization wind speed retrieval. IEEE Geoscience and Remote Sensing Letters 8:456–459, https://doi.org/10.1109/LGRS.2010.2085417. 
  24. Valenzuela, G.R. 1978. Theories for the interaction of electromagnetic and oceanic waves – A review. Boundary-Layer Meteorology 13:61–85, https://doi.org/10.1007/BF00913863.
  25. van Zadelhoff, G.-J., A. Stoffelen, P.W. Vachon, J. Wolfe, J. Horstmann, and M. Belmonte Rivas. 2013. Scatterometer hurricane wind speed retrievals using cross polarization. Atmospheric Measurement Techniques Discussions 6:7,945–7,984, https://doi.org/​10.5194/amtd-6-7945-2013.
  26. Wackerman, C., C. Rufenach, R. Schuchman, J. Johannessen, and K. Davidson. 1996. Wind vector retrieval using ERS-1 synthetic aperture radar imagery. IEEE Transactions on Geoscience and Remote Sensing 34:1,343–1,352, https://doi.org/10.1109/36.544558.
  27. Wright, J.W. 1968. A new model for sea clutter. IEEE Transactions Antennas and Propagation 16(2): 217–223, https://doi.org/​10.1109/TAP.1968.1139147.
  28. Zhang, B., W. Perrie, and Y. He. 2011. Wind speed retrieval from RADARSAT-2 quad-polarization images using a new polarization ratio model. Journal of Geophysical Research 116, C08008, https://doi.org/10.1029/2010JC006522. 
Copyright & Usage

This is an open access article made available under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution, and reproduction in any medium or format as long as users cite the materials appropriately, provide a link to the Creative Commons license, and indicate the changes that were made to the original content. Images, animations, videos, or other third-party material used in articles are included in the Creative Commons license unless indicated otherwise in a credit line to the material. If the material is not included in the article’s Creative Commons license, users will need to obtain permission directly from the license holder to reproduce the material.