Retrieval and Quality Assessment of Wind Velocity Vectors on the Ocean With C-Band SAR
Journal article, 2014

Wind vector fields derived from synthetic aperture radar (SAR) sensors show variations at smaller scales than most other globally available surface wind sources. However, few studies have been devoted to the investigation of the accuracy of SAR-derived wind fields at different scales and how they compare with other wind data. In order to investigate these issues, an algorithm for the retrieval of SAR-derived wind vectors has been developed, and a quality assessment between the retrievals and in situ, scatterometer, and numerical weather model (NWM) wind data has been performed. The implemented wind retrieval algorithm detects streak features in the SAR image to estimate wind directions and inverts wind speeds using CMOD-IFR2, CMOD5, or CMOD5.N geophysical model functions. In addition, a regularization method for filtering outliers in the wind direction retrievals is used. Retrievals compared with in situ data indicated better performance at offshore locations for wind speed inversions with CMOD5.N. The bias and standard deviation for offshore regularized wind directions and CMOD5.N speeds are 9 degrees and 25 degrees and -0.1 and 1.4 m/s, respectively. The comparison with the scatterometer and NWM wind data has been performed for retrievals at 5-, 10-, and 20-km resolution. The results indicate a better agreement of the coarser retrievals with the reference data. Nevertheless, mapping of smaller scale features requires wind directions from the SAR image itself.

synthetic aperture radar (SAR)

wind speed

wind direction variation with resolution

ocean surface wind

scatterometer

numerical weather model (NWM)

Directional variation

wind direction

Author

Gisela Carvajal

Chalmers, Earth and Space Sciences, Radar Remote Sensing

Leif Eriksson

Chalmers, Earth and Space Sciences, Radar Remote Sensing

Lars Ulander

Chalmers, Earth and Space Sciences, Radar Remote Sensing

IEEE Transactions on Geoscience and Remote Sensing

0196-2892 (ISSN)

Vol. 52 5 2519-2537

Subject Categories

Geophysics

DOI

10.1109/tgrs.2013.2262377

More information

Created

10/7/2017