## 6 Conclusions  
This study conducted a systematic comparison of wind field retrieval accuracy between the direct inversion method and three VAM approaches, utilizing 1803 Sentinel-1 VV polarized level-2 OCN images. The ERA5 reanalysis wind field served as the background, and validation was performed against NDBC buoy measurements. Regarding wind speed accuracy, within the study area, VAM3 (\(J_{\text{NFRCS+DCA}}\)) that considers both NRCS and DCA achieves a wind speed RMSE of 1.42 m/s, outperforming the direct retrieval method with an RMSE of 1.52 m/s, VAM1 (\(J_{\text{NFRCS}}\)) considering only NRCS  
Figure 10: (**a**) Comparison of ERA5 wind speed with buoy-measured wind speed and (**b**) the bias of ERA5 wind speed before and after correction with buoy-measured wind speed as a function of wind speed. with an RMSE of 1.43 m/s, and VAM2 (\(I_{DCA}\)) considering only DCA with an RMSE of 2.01 m/s, across a wind speed range of up to 23.2 m/s. This method achieves optimal performance within moderate wind speed ranges. However, its wind speed retrieval bias exhibits a gradual increase when wind speeds exceed 11 m/s. This phenomenon is mainly caused by the systematic bias inherent in the background wind field employed in variational analysis during high-wind-speed conditions. Following the correction of background wind field errors, the method achieves superior performance across different wind speed ranges. Furthermore, the observed increase in RMSE at higher wind speeds could be attributed to the diminished sensitivity of VV co-polarized signals under such conditions, resulting in reduced accuracy when performing wind speed inversion using CMD5.N [15]. In terms of wind direction retrieval, VAM3 (\(I_{NRCS+DCA}\)) achieved a wind direction RMSE of 26.00\({}^{\circ}\), similar to VAM2 (\(I_{DCA}\)) with an RMSE of 26.05\({}^{\circ}\), and better than the direct retrieval method with an RMSE of 27.25\({}^{\circ}\) and VAM1 (\(J_{NRCS}\)) with an RMSE of 27.66\({}^{\circ}\). This highlights the critical role of DCA information in enhancing wind direction retrieval accuracy. However, it is noteworthy that in the VAMs utilized in this study, the improvement of background wind speed has a limited effect on the accuracy of wind direction retrieval. Drawing from a thorough analysis of the wind speed retrieval outcomes presented above, the VAM that effectively combines DCA and NRCS demonstrates the capability to achieve optimal accuracy in retrieving both wind speed and direction. In future work, we plan to expand the dataset of Sentinel-1 VV polarization level-2 OCN products to further evaluate the performance of VAM under high-wind-speed conditions. In addition, due to the fitting limitations of CMOD5.N in high-wind-speed regimes, incorporating cross-polarized NRCS measurements will be explored to improve high-wind-speed retrieval accuracy. These enhancements are expected to further refine the applicability of this method to Sentinel-1 data. [PERSON] was primarily responsible for data collection, processing and analysis, and completed the first draft of the manuscript; [PERSON] was responsible for the overall conceptualization and the design of the research, and supervised the entire research process; [PERSON] assisted in manuscript revision and refinement; [PERSON] and [PERSON] participated in data collection and were responsible for the visualization of experimental results; [PERSON] contributed to data analysis and interpretation. All authors have read and agreed to the published version of the manuscript.