Abstract
In this paper, the sea surface wind speed (SSWS) retrieval from Gaofen-3 (GF-3) quad-polarization stripmap (QPS) data in vertical-vertical (VV), horizontal-horizontal (HH), and vertical-horizontal (VH) polarizations is investigated in detail based on 3170 scenes acquired from October 2016 to May 2018. The radiometric calibration factor of the VV polarization data is examined first. This calibration factor generally meets the requirement of SSWS retrieval accuracy with an absolute bias of less than 0.5 m/s but shows highly dispersed characteristics. These results lead to SSWS retrievals with a small bias of 0.18 m/s, but a rather high root mean square error (RMSE) of 2.36 m/s when compared with the ERA-Interim reanalysis model data. Two refitted polarization ratio (PR) models for the QPS HH polarization data are presented. Based on a combination of the incidence angle-dependent and azimuth angle-dependent PR model and CMOD5.N, the SSWS derived from the QPS HH data shows a bias of 0.07 m/s and an RMSE of 2.26 m/s relative to the ERA-Interim reanalysis model wind speed. A linear function relating SSWS and the normalized radar cross section (NRCS) of QPS VH data is derived. The SSWS data retrieved from the QPS VH data show good agreement with the WindSat SSWS data, with a bias of 0.1 m/s and an RMSE of 2.02 m/s. We also apply the linear function to the GF-3 Wide ScanSAR data acquired for the typhoon SOULIK, which yields very good agreement with the model results. A comparison of SSWS retrievals among three different polarization datasets is also presented. The current study and our previous work demonstrate that the general accuracy of the SSWS retrieval based on GF-3 QPS data has an absolute bias of less than 0.3 m/s and an RMSE of 2.0 ± 0.2 m/s relative to various datasets. Further improvement will depend on dedicated radiometric calibration efforts.
Highlights
Ocean wind is the major force of global ocean circulation [1] and is typically measured by anemometers onboard buoys, platforms, and ships very close to the sea surface
sea surface wind (SSW) directions have been derived from images acquired by various spaceborne synthetic aperture radar (SAR) missions, e.g., ERS/SAR, ENVISAT/ASAR, and TerraSAR-X, using either the fast Fourier transform (FFT) method [5] or the local gradient (LG) method [6,7]
By comparing with buoy measurements and ERA-Interim reanalysis wind speed, Shao et al [43] acquired an root mean square error (RMSE) of 1.4–2.0 m/s when the VV polarization data were used for sea surface wind speed (SSWS) retrieval, while the RMSE values for the HH polarization results were slightly higher when the polarization ratio (PR) model developed by Zhang et al [25] was applied
Summary
Ocean wind is the major force of global ocean circulation [1] and is typically measured by anemometers onboard buoys, platforms, and ships very close to the sea surface. Retrieval of SSW from active remote sensors, e.g., scatterometer and SAR instruments, is widely based on the geophysical model function (GMF), which empirically relates SSW speed (SSWS), direction, and radar geometry (incidence angle) to the measured radar backscatter. Spaceborne SAR generally can yield SSWS retrieval with an accuracy of approximately less than 0.5 m/s (in terms of bias in comparison with buoy data, scatterometer measurements, and reanalysis model results [26,27,28]) for SSWSs of less than 20–25 m/s. By comparing with buoy measurements and ERA-Interim reanalysis wind speed, Shao et al [43] acquired an RMSE of 1.4–2.0 m/s when the VV polarization data were used for SSWS retrieval, while the RMSE values for the HH polarization results were slightly higher when the PR model developed by Zhang et al [25] was applied
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