Synchronous Wind and Wave Monitoring by Gaofen-3 SAR During Tropical Cyclones

This letter aims to assess the applicability of synchronous wind and wave observations using Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) during tropical cyclones (TCs) in the North West Pacific (NWP). From 2023 to 2024, 28 GF-3 images featuring visible TC eyes were available for this study. The well-known machine learning method, denoted as eXtreme Gradient Boosting (XGBoost), is implemented to retrieve sea surface wind and significant wave height (SWH) from dual-polarized GF-3 images acquired in Wide ScanSAR (WSC) mode. The inversion is supported by 20 GF-3 images collocated with re-constructed winds based on European Centre for Medium-Range Weather Forecasts (ECMWFs) reanalysis (ERA-5) data and Japan Meteorological Agency (JMA) best-track data, along with SWH simulations from the WAVEWATCH-III (WW3). Wind speeds inverted from additional 8 GF-3 images are validated against soil moisture active passive (SMAP) measurements, yielding a root mean squared error (RMSE) of 3.31 m/s, a correlation (COR) of 0.80, and a scatter index (SI) of 0.29. The SWHs inverted from eight images are compared with Haiyang-2 (HY-2) altimeter data and WW3 simulations, showing an RMSE of 0.74 m, a COR of 0.83, and an SI of 0.25. Our study demonstrates the robustness of GF-3 SAR in monitoring extreme sea states.