Abstract
The principal purpose of this paper is to extract entire sea surface wind’s information from spaceborne lidar, and particularly to utilize a appropriate algorithm for removing the interference information due to whitecaps and subsurface water. Wind speeds are obtained through empirical relationship with sea surface mean square slopes. Wind directions are derived from relationship between wind speeds and wind directions implied in CMOD5n geophysical models function (GMF). Whitecaps backscattering signals were distinguished with the help of lidar depolarization ratio measurements and rectified by whitecaps coverage equation. Subsurface water backscattering signals were corrected by means of inverse distance weighted (IDW) from neighborhood non-singular data with optimal subsurface water backscattering calibration parameters. To verify the algorithm reliably, it selected NDBC’s TAO buoy-laying area as survey region in camparison with buoys’ wind field data and METOP satellite ASCAT of 25 km single orbit wind field data after temporal-spatial matching. Validation results showed that the retrieval algorithm works well in terms of root mean square error (RMSE) less than 2m/s and wind direction’s RMSE less than 21 degree.
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Wang, T., Pan, D., He, X. et al. Wind vector retrieval algorithm from spaceborne lidar data. Acta Oceanol. Sin. 33, 129–135 (2014). https://doi.org/10.1007/s13131-014-0448-z
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DOI: https://doi.org/10.1007/s13131-014-0448-z