{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T21:29:56Z","timestamp":1774387796649,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2018,9,11]],"date-time":"2018-09-11T00:00:00Z","timestamp":1536624000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Key R&amp;D Program of China","award":["2016YFC1401007"],"award-info":[{"award-number":["2016YFC1401007"]}]},{"name":"the Global Change Research Program of China","award":["2015CB953901"],"award-info":[{"award-number":["2015CB953901"]}]},{"name":"the National Natural Science Foundation of China project","award":["41776181"],"award-info":[{"award-number":["41776181"]}]},{"name":"the Postgraduate Research&amp;Practice Innovation Program of Jiangsu Province","award":["KYCX18_1012"],"award-info":[{"award-number":["KYCX18_1012"]}]},{"name":"the National Natural Science Youth Foundation of China","award":["41706193"],"award-info":[{"award-number":["41706193"]}]},{"name":"the Canadian Office of Energy Research and Development","award":["1B00.003C"],"award-info":[{"award-number":["1B00.003C"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This work discusses the accuracy of C-2PO (C-band cross-polarized ocean backscatter) and CMOD4 (C-band model) geophysical model functions (GMF) for sea surface wind speed retrieval from satellite-born Synthetic Aperture Radar (SAR) images over in the Northwest Pacific off the coast of China. In situ observations are used for comparison of the retrieved wind speed using two established wind retrieval models: C-2PO model and CMOD4 GMF. Using 439 samples from 92 RADARSAT-2 fine quad-polarization SAR images and corresponding reference winds, we created two subset wind speed databases: the training and testing subsets. From the training data subset, we retrieve ocean surface wind speeds (OSWSs) from different models at each polarization and compare with reference wind speeds. The RMSEs of SAR-retrieved wind speeds are: 2.5 m\/s: 2.11 m\/s (VH-polarized), 2.13 m\/s (HV-polarized), 1.86 m\/s (VV-polarized) and 2.26 m\/s (HH-polarized) and the correlation coefficients are 0.86 (VH-polarized), 0.85(HV-polarized), 0.87(VV-polarized) and 0.83 (HH-polarized), which are statistically significant at the 99.9% significance level. Moreover, we found that OSWSs retrieved using C-2PO model at VH-polarized are most suitable for moderate-to-high winds while CMOD4 GMF at VV-polarized tend to be best for low-to-moderate winds. A hybrid wind retrieval model is put forward composed of the two models, C-2PO and CMOD4 and sets of SAR test data are used in order to establish an appropriate wind speed threshold, to differentiate the wind speed range appropriate for one model from that of the other. The results show that the OSWSs retrieved using our hybrid method has RMSE of 1.66 m\/s and the correlation coefficient are 0.9, thereby significantly outperforming both the C-2PO and CMOD4 models.<\/jats:p>","DOI":"10.3390\/rs10091448","type":"journal-article","created":{"date-parts":[[2018,9,11]],"date-time":"2018-09-11T11:40:02Z","timestamp":1536666002000},"page":"1448","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Comparison of C-Band Quad-Polarization Synthetic Aperture Radar Wind Retrieval Models"],"prefix":"10.3390","volume":"10","author":[{"given":"He","family":"Fang","sequence":"first","affiliation":[{"name":"School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"Fisheries &amp; Oceans Canada, Bedford Institute of Oceanography, Dartmouth, NS B2Y 4A2, Canada"}]},{"given":"Tao","family":"Xie","sequence":"additional","affiliation":[{"name":"School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China"},{"name":"Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China"}]},{"given":"William","family":"Perrie","sequence":"additional","affiliation":[{"name":"Fisheries &amp; Oceans Canada, Bedford Institute of Oceanography, Dartmouth, NS B2Y 4A2, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4984-3925","authenticated-orcid":false,"given":"Guosheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Fisheries &amp; Oceans Canada, Bedford Institute of Oceanography, Dartmouth, NS B2Y 4A2, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7514-3212","authenticated-orcid":false,"given":"Jingsong","family":"Yang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, State Oceanic Administration, Hangzhou 310012, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1531-5262","authenticated-orcid":false,"given":"Yijun","family":"He","sequence":"additional","affiliation":[{"name":"School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,9,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1175\/BAMS-D-12-00165.1","article-title":"Ocean wind speed climatology from spaceborne SAR imagery","volume":"95","author":"Monaldo","year":"2014","journal-title":"Bull. 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