In this study, we analyzed the ocean surface wind speed dependence of off‐nadir data from the Surface Waves Investigation and Monitoring (SWIM) aboard the Chinese‐French Oceanography Satellite (CFOSAT). When the data were analyzed, the SWIM normalized radar cross section (NRCS) at most incidence angles decreased along the NCEP Global Forecast System wind speed. This trend is consistent with that in a Ku‐band geophysical model function at low incidence angles (KuLMOD2S), although there was a systematic bias between the two. The consistency indicates that the SWIM data quality was normal in terms of wind speed dependence. The bias was recalibrated using a numerical weather prediction‐based ocean calibration method and the wind speeds were retrieved from the recalibrated NRCS data using the KuLMOD2S model. Finally, the retrievals at off‐nadir as well as the wind products at nadir were validated using collocated CFOSAT scatterometer (CSCAT) wind measurements. When the results were validated, the retrievals at 0.5° were consistent with the averaged wind products at nadir and both had a root mean square difference (RMSD) around 1.4 m/s compared to the CSCAT winds. Moreover, the winds retrieved from the SWIM data at most incidence angles were in good agreement with the CSCAT winds,and the RMSD values were within 2.0 m/s for incidence angles less than 7.5°, although the retrieval accuracy was poor at larger incidence angles. These results demonstrate that the SWIM data at incidence angles below 7.5° have an ability to retrieve the wind speed.

In this study, sea surface wind speed was retrieved using the Global Precipitation Measurement (GPM) dual-frequency precipitation radar (DPR) Ka-band data. In order to establish the Ka-band model at low incidence angles, the dependence of the DPR Ka-band normalized radar cross section (NRCS) on the wind speed, incidence angle, sea surface temperature (SST), significant wave height (SWH), and sea surface current speed (CSPD) was analyzed first. We confirmed that the normalized radar cross section depends on the wind speed, incidence angle, and SST. Second, an empirical model at low incidence angles was established. This model links the Ka-band NRCS to the incidence angle, wind speed, and SST. Additionally, the wind speed was retrieved by the model and was validated via the GPM Microwave Imager (GMI) wind product. The validation yielded a root mean square error (RMSE) of 1.45 m/s and the RMSE was better at a lower incidence angle and a higher SST. This model may expand the use of GPM DPR data in enriching the sea surface wind speed data set. It is also helpful for other Ka-band spaceborne radars at low incidence angles to measure wind speed in the future.

In this study, the Gaofen-3 synthetic aperture radar (GF-3SAR) wave mode data were recalibrated, and were further used to retrieve the ocean surface wind. The collocated data used include the European Center for Medium-Range Weather Forecast (ECMWF) and the Advanced Scatterometer (ASCAT) wind data. First, the GF-3 data were recalibrated using a numerical weather prediction (NWP) method. Here the GF-3 measured normalized radar cross section (NRCS) were compared to the simulated NRCS (by collocated ECMWF winds and CMOD5.N model) to determine the recalibration coefficients at different polarizations and incidence angles. By the recalibration, the bias between the GF-3 NRCS and the simulated NRCS was significantly reduced (&0.1dB). Then, the wind speed and wind direction were retrieved from the recalibrated GF-3 data by the CMOD5.N model using the optimal scheme (co-polarized data, VV and HH data) and linear model (cross-polarized data, VH and HV data). Note that the cross-polarized data were only used to retrieved wind speed due to the weak sensitivity on wind direction. Finally, the wind retrievals were validated by the collocated ASCAT winds. The bias and root mean square error (RMSE) of the wind retrievals were obtained at different polarizations and incidence angles. From the validations, the retrieved wind speed and direction have better accuracies than the ones before recalibration. Take the retrieval accuracy at incidence angles from 40° to 40.7° as an example, the RMSEs are 1.89 m/s, 1.92m/s, 2.07m/s and 2.12 m/s for VV, HH, VH, HV data respectively. Moreover, for wind speed retrievals at all incidence angles, the RMSEs are around 2 m/s, while the RMSEs from cross-polarized data are slightly larger than the ones from co-polarized data. For retrieved wind direction, the RMSEs from co-polarized data are lower than 20° Results indicate that the NWP-based recalibration method can significantly improve the accuracy of GF-3 wind retrievals.