Although cross-polarized synthetic aperture radar (SAR) images play a crucial role in wind speed retrieval under extreme weather conditions, the retrieved wind speeds are susceptible to thermal noise. However, there is still a lack of research on how thermal noise affects the accuracy of wind speed retrieval. To address this issue, this paper proposes a strategy to quantitatively examine the impact of thermal noise on wind speed retrieval, using 910 Sentinel-1 cross-polarized SAR images acquired in Extra-Wide Swath (EW) mode. The thermal noise and wind speeds of these images range from -35 dB to -22.5 dB and from 5 m/s to 70 m/s, respectively. By considering the wind speed retrieved from dual-polarized SAR as a reference, the study reveals that higher levels of thermal noise result in increased uncertainty in the retrieved wind speeds using cross-polarized SAR images. Additionally, the error of wind speed retrieval from cross-polarized SAR rapidly decreases as wind speed increases, eventually converging to a stable level. Notably, as thermal noise levels decrease to less than -30 dB for wind speeds between 5 m/s and 25 m/s, the root-mean-square error (RMSE) associated with wind speed retrieval through cross-polarized SAR imagery experiences a rapid decline, with a 94% reduction in RMSE, which then stabilizes. This implies that when the thermal noise level falls below -30 dB, wind speed retrieval can be directly conducted using cross-polarized imagery for wind speeds exceeding those typical of a tropical storm, yielding comparable results to dual-polarized imagery. The findings of this study provide valuable insights for advancing wind speed retrieval algorithms and hold significant reference value for the design of the next-generation radar instruments that will incorporate the cross-polarized channel.

Sea surface wind retrieval methods using synthetic aperture radar (SAR) are generally classified into two categories: the direct inversion method and the variational analysis method (VAM). Traditional VAM retrieves wind fields by integrating background wind information with SAR normalized radar cross-section (NRCS). Recent studies have shown that incorporating SAR Doppler centroid anomaly (DCA) as an additional observation for variational analysis can improve the accuracy of wind speed and direction retrieval. However, this method has yet to be systematically evaluated, particularly with respect to its applicability to Sentinel-1 SAR data. This study presents a comprehensive assessment based on 1803 Sentinel-1 vertical–vertical (VV) polarization level-2 Ocean (OCN) product scenes collocated with in situ measurements from the National Data Buoy Center (NDBC), yielding a total of 2826 matched data pairs. We systematically evaluate the performance of three distinct VAM configurations: VAM1 (J_NRCS), utilizing only NRCS; VAM2 (J_DCA), employing solely DCA; and VAM3 (J_NRCS+DCA), which combines both NRCS and DCA. The results demonstrate that VAM3 (J_NRCS+DCA) achieves the best performance, with the lowest root mean square error (RMSE) of 1.42 m/s for wind speed and 26.00° for wind direction across wind speeds up to 23.2 m/s, outperforming both VAM1 (J_NRCS) and VAM2 (J_DCA). Furthermore, the accuracy of background wind speed is identified as a critical factor affecting VAM performance. After correcting the background wind speed, the RMSE and bias of the retrieved wind speed decreased significantly across all VAMs. The most notable bias reduction was observed at wind speeds exceeding 10 m/s. These findings provide essential theoretical support for the operational application of Sentinel-1 OCN products in sea surface wind retrieval.