The goal of this study was to investigate the performance of a spectral-transformation wave retrieval algorithm and confirm the accuracy of wave retrieval from C-band Chinese Gaofen-3(GF-3)Synthetic Aperture Radar(SAR...The goal of this study was to investigate the performance of a spectral-transformation wave retrieval algorithm and confirm the accuracy of wave retrieval from C-band Chinese Gaofen-3(GF-3)Synthetic Aperture Radar(SAR)images.More than 200 GF-3 SAR images of the coastal China Sea and the Japan Sea for dates from January to July 2020 were acquired in the Quad-Polarization Strip(QPS)mode.The images had a swath of 30 km and a spatial resolution of 8 m pixel size.They were processed to retrieve Significant Wave Height(SWH),which is simulated from a numerical wave model called Simulating WAves Nearshore(SWAN).The first-guess spectrum is essential to the accuracy of Synthetic Aperture Radar(SAR)wave spectrum retrieval.Therefore,we proposed a wave retrieval scheme combining the theocratic-based Max Planck Institute Algorithm(MPI),a Semi-Parametric Retrieval Algorithm(SPRA),and the Parameterized First-guess Spectrum Method(PFSM),in which a full wave-number spectrum and a non-empirical ocean spectrum proposed by Elfouhaily are applied.The PFSM can be driven using the wind speed without calculating the dominant wave phase speed.Wind speeds were retrieved using a Vertical-Vertical(VV)polarized geophysical model function C-SARMOD2.The proposed algorithm was implemented for all collected SAR images.A comparison of SAR-derived wind speeds with European Center for Medium-Range Weather Forecasts(ECMWF)ERA-5 data showed a 1.95 m/s Root-Mean-Squared Error(RMSE).The comparison of retrieved SWH with SWAN-simulated results demonstrated a 0.47 m RMSE,which is less than the 0.68 m RMSE of SWH when using the PFSM algorithm.展开更多
基金supported by the Key Special Project for Introduced Talents Team of the Southern Marine Science and Engineering Guangdong Laboratory(Guangzhou)[Grant No GML2019ZD0302]the National Natural Science Foundation of China[Grant Nos 41806005 and 42076238]the China Postdoctoral Science Foundation[Grant No 2020M670245].
文摘The goal of this study was to investigate the performance of a spectral-transformation wave retrieval algorithm and confirm the accuracy of wave retrieval from C-band Chinese Gaofen-3(GF-3)Synthetic Aperture Radar(SAR)images.More than 200 GF-3 SAR images of the coastal China Sea and the Japan Sea for dates from January to July 2020 were acquired in the Quad-Polarization Strip(QPS)mode.The images had a swath of 30 km and a spatial resolution of 8 m pixel size.They were processed to retrieve Significant Wave Height(SWH),which is simulated from a numerical wave model called Simulating WAves Nearshore(SWAN).The first-guess spectrum is essential to the accuracy of Synthetic Aperture Radar(SAR)wave spectrum retrieval.Therefore,we proposed a wave retrieval scheme combining the theocratic-based Max Planck Institute Algorithm(MPI),a Semi-Parametric Retrieval Algorithm(SPRA),and the Parameterized First-guess Spectrum Method(PFSM),in which a full wave-number spectrum and a non-empirical ocean spectrum proposed by Elfouhaily are applied.The PFSM can be driven using the wind speed without calculating the dominant wave phase speed.Wind speeds were retrieved using a Vertical-Vertical(VV)polarized geophysical model function C-SARMOD2.The proposed algorithm was implemented for all collected SAR images.A comparison of SAR-derived wind speeds with European Center for Medium-Range Weather Forecasts(ECMWF)ERA-5 data showed a 1.95 m/s Root-Mean-Squared Error(RMSE).The comparison of retrieved SWH with SWAN-simulated results demonstrated a 0.47 m RMSE,which is less than the 0.68 m RMSE of SWH when using the PFSM algorithm.
