Abstract
The synthetic aperture radar (SAR) has been proven to be a valuable tool for high resolution ocean surface wind measurements, which is especially important for coastal waters. However, oceanic surface phenomena observed by SAR and oceanic processes which can cause the change of backscatter in SAR imagery will influence the SAR wind retrieval. Upwelling is one of the main factors and it is prevalent in summer along the Zhejiang Coast. It smoothes the sea surface which results in the lower backscatter cross section in SAR imagery. In this article, using sea surface temperature (SST) and chlorophyll2-a data derived from EOS MODIS, the low backscatter features in ENVISAT ASAR imagery are analyzed along the Zhejiang Coast in the East China Sea. And then CMOD4 algorithm is adopted to retrieve the sea surface wind speed, using wind directions from interpolated NCEP / NCAR reanalysis data. The result of wind speed is negatively biased due to the low Normalized Radar Cross Section (NRCS) associated with the Zhejiang Coastal Upwelling. In order to resolve impact of the coastal upwelling on SAR wind retrieval, combining high resolution numerical meteorological model wind field data, a wind speed correction model is proposed using linear robust regression. Results show that the accuracy of SAR wind retrieval is improved in upwelling region.
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