{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:57:09Z","timestamp":1760151429898,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,3,17]],"date-time":"2022-03-17T00:00:00Z","timestamp":1647475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Lei Guan","award":["2019YFA0607001"],"award-info":[{"award-number":["2019YFA0607001"]}]},{"name":"Zhuomin Li","award":["HSPHDSRF-2022-02-001"],"award-info":[{"award-number":["HSPHDSRF-2022-02-001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The visible and infrared scanning radiometer (VIRR) onboard the Fengyun-3C (FY-3C) meteorological satellite has 11 \u03bcm and 12 \u03bcm channels, which are capable of sea surface temperature (SST) observations. This study is based on atmospheric radiative transfer modeling (RTM) by applying Bayesian cloud detection theory and optimal estimation (OE) to obtain sea surface skin temperature (SSTskin) from VIRR in the Northwest Pacific. The inter-calibration of FY-3C\/VIRR 11 \u03bcm and 12 \u03bcm brightness temperature (BT) is carried out using the Moderate Resolution Imaging Spectroradiometer (MODIS) as the reference sensor. Bayesian cloud detection and OE SST retrieval with the calibration BT data is performed to obtain SSTskin. The SSTskin retrievals are compared with the buoy SST with a temporal window of 1 h and a spatial window of 0.01\u00b0. The bias is \u22120.12 \u00b0C, and the standard deviation is 0.52 \u00b0C. Comparisons of the retrieved SSTskin with the AVHRR (Advanced Very High Resolution Radiometer) SSTskin from European Space Agency Sea Surface Temperature Climate Change Initiative (ESA SST CCI) project show the bias of 0.08 \u00b0C and the standard deviation of 0.55 \u00b0C. The results indicate that the VIRR SSTskin are consistent with AVHRR SSTskin and buoy SST.<\/jats:p>","DOI":"10.3390\/rs14061451","type":"journal-article","created":{"date-parts":[[2022,3,20]],"date-time":"2022-03-20T21:37:17Z","timestamp":1647812237000},"page":"1451","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Sea Surface Skin Temperature Retrieval from FY-3C\/VIRR"],"prefix":"10.3390","volume":"14","author":[{"given":"Zhuomin","family":"Li","sequence":"first","affiliation":[{"name":"Sanya Oceanographic Institution, Ocean University of China, Sanya 572024, China"},{"name":"Faculty of Information Science and Engineering, College of Marine Technology, Ocean University of China, Qingdao 266100, China"},{"name":"Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China"}]},{"given":"Mingkun","family":"Liu","sequence":"additional","affiliation":[{"name":"Sanya Oceanographic Institution, Ocean University of China, Sanya 572024, China"},{"name":"Faculty of Information Science and Engineering, College of Marine Technology, Ocean University of China, Qingdao 266100, China"},{"name":"Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China"}]},{"given":"Sujuan","family":"Wang","sequence":"additional","affiliation":[{"name":"National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China"}]},{"given":"Liqin","family":"Qu","sequence":"additional","affiliation":[{"name":"Sanya Oceanographic Institution, Ocean University of China, Sanya 572024, China"},{"name":"Faculty of Information Science and Engineering, College of Marine Technology, Ocean University of China, Qingdao 266100, China"},{"name":"Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9902-8035","authenticated-orcid":false,"given":"Lei","family":"Guan","sequence":"additional","affiliation":[{"name":"Sanya Oceanographic Institution, Ocean University of China, Sanya 572024, China"},{"name":"Faculty of Information Science and Engineering, College of Marine Technology, Ocean University of China, Qingdao 266100, China"},{"name":"Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1175\/1520-0442(1993)006<1545:EAERPP>2.0.CO;2","article-title":"ENSO and ENSO-related Predictability. 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