An Empirical Algorithm to Retrieve Significant Wave Height from Sentinel-1 Synthetic Aperture Radar Imagery Collected under Cyclonic Conditions

被引:24
|
作者
Shao, Weizeng [1 ,2 ]
Hu, Yuyi [1 ]
Yang, Jingsong [2 ]
Nunziata, Ferdinando [3 ]
Sun, Jian [4 ]
Li, Huan [5 ]
Zuo, Juncheng [1 ]
机构
[1] Zhejiang Ocean Univ, Marine Sci & Technol Coll, Zhoushan 316000, Peoples R China
[2] State Ocean Adm, Inst Oceanog 2, State Key Lab Satellite Ocean Environm Dynam, Hangzhou 310012, Zhejiang, Peoples R China
[3] Univ Napoli Parthenope, Dipartimento Ingn, I-80133 Naples, Italy
[4] Ocean Univ China, Phys Oceanog Lab, Qingdao 266100, Peoples R China
[5] Natl Marine Data & Informat Serv, Tianjin 300171, Peoples R China
基金
中国国家自然科学基金;
关键词
significant wave height; Sentinel-1 synthetic aperture radar; cyclone; SPACE-BORNE; OCEAN; WIND; BAND; VALIDATION; SPECTRA; CLIMATE; SYSTEM; CUTOFF; MODEL;
D O I
10.3390/rs10091367
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this study, an empirical algorithm is proposed to retrieve significant wave height (SWH) from dual-polarization Sentinel-1 (S-1) synthetic aperture radar (SAR) imagery collected under cyclonic conditions. The retrieval scheme is based on the well-known CWAVE empirical function that is here updated to deal with multi-polarization S-1 SAR measurements collected using the interferometric wide (IW) and the Extra Wide-Swath (EW) imaging modes, under cyclonic conditions. First, a training dataset that consists of six S-1 SAR images collected under cyclonic conditions is exploited to both tune the retrieval function and to check the soundness of the retrievals against the co-located WAVEWATCH-III (WW3) numerical simulations. The comparison of simulation from the WW3 model and measurements from altimeter Jason-2 shows a 0.29m root mean square error (RMSE) of significant wave height (SWH). Then, a testing data-set that consists of two S-1 SAR images is exploited to provide a preliminary validation. The results, verified against both WW3 and European Centre for Medium-Range Weather Forecasts (ECMWF) data, show the soundness of the herein approach.
引用
收藏
页数:17
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