# First Assessment of GF3-02 SAR Ocean Wind Retrieval
## 1 Introduction  
As an important marine environmental parameter, the sea surface wind field affects ocean dynamic processes such as sea wave formation, water mass composition, and wave motion. In recent years, the research on the efficient and high-precision acquisition method of wind field information on the vast ocean surface has become a research direction of great concern in marine environmental monitoring and the development and utilization of marine resources. The development of Synthetic Aperture Radar (SAR) plays a vital role in the remote sensing of ocean surface characteristics. It can carry out all-weather high-resolution and large-area dynamic monitoring of the global surface. The SAR-derived normalized radar cross-sections (NRCS) on the sea surface are mainly caused by Bragg scattering [1], which is caused by the resonance interaction between the magnetic wave emitted by the radar and the centimeter-scale short wave, and is mainly related to the radar parameters and the characteristics of the sea surface. In recent years, scholars in ocean remote sensing worldwide have carried out much extensive research on thecharacteristics of SAR wind field retrieval based on microwave scatterometer wind field retrieval algorithm. At present, Geophysical Model Function (GMF) is the most widely used wind speed retrieval algorithm, an empirical formula that combines the NRCS with the wind speed and direction at 10 m above sea level and the incident angle of the radar. The CMOD series models suitable for C-band VV polarization data are the most mature. According to the scatterometer data, CMOD2 [2], CMOD4 [3], CMOD-IFR2 [4], CMOD5 [5], CMOD5.N [6], C2013 [7], CMOD5.H [8], CMOD7 [9], etc. have been developed successively. For HH polarization, the HH polarization NRCS is transformed into VV polarization NRCS by polarization ratio (PR), and then the GMFs mode function of VV polarization is used to retrieve the sea surface wind speed. For example, [PERSON] [10], [PERSON] [11], and [PERSON] et al. [12] put forward the PR formula only related to the incident angle. [PERSON] et al. [13] obtained a PR model suitable for Gaofen-3 (GF-3) SAR by fitting the \(\alpha\) parameter of the PR model proposed by [PERSON] through GF-3 qual-polarization data. [PERSON] et al. [14] found that the polarization ratio PR is modulated by the relative wind direction. According to this property, they proposed a PR model related to the incident angle and the relative wind direction. Similarly, [PERSON] [15] used GF-3 SAR data to establish a PR model related to the incident angle and relative wind direction. In recent decades, these GMFs models have been successfully applied to the retrieval of wind speed by C-band satellites such as ERS-1/2 [16], ENVISAT ASAR, Radarsat-1/2, Sentinel-1A/B, and GF-3. [PERSON] et al. [17] used CMOD-IFR2 to retrieve the wind speed from the ENVISAT ASAR image, and root mean square errors (RMSE) of the retrieval wind speed and the NCEP/QSCAT mixed wind vector were 1.9 m/s and 1.6 m/s, respectively. [PERSON] et al. [18] compared the RMSE of wind speed retrieval of Radarsat-2 by different GMFs, and considered CMOD5 to be the optimal wind speed retrieval model. [PERSON] et al. [19] used CMOD5.N to verify the wind speed of the Sentinel-1A SAR image, and the RMSE of the estimated wind speed and ASCAT scatterometer wind field product was 1.42 m/s. [PERSON] et al. [20] used the GF-3 SAR data to retrieve the wind field and compared it with the buoy wind field data. The results showed that the wind speed RMSE was 2.46 m/s and the wind direction RMSE was 22.22\({}^{\circ}\). With the accumulation of SAR data, CSARMOD [21], CSARMOD2 [22], and CMODH [23] models are developed using SAR data. In [23], [PERSON] not only proposed a CMODH model for SAR HH polarization data, which we call CMODH_HH in this paper, but also derived a set of model coefficients suitable for VV polarization data, which we called CMODH_VV.