{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T02:23:59Z","timestamp":1774923839116,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,5,5]],"date-time":"2023-05-05T00:00:00Z","timestamp":1683244800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"CMA Special Fund for Scientific Research in the Public Interest","award":["GYHY201406001-01"],"award-info":[{"award-number":["GYHY201406001-01"]}]},{"name":"The Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III)","award":["GYHY201406001-01"],"award-info":[{"award-number":["GYHY201406001-01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The thermal infrared data of Fengyun 4A (FY-4A) geostationary meteorological satellite can be used to retrieve hourly land surface temperature (LST). In this paper, seven candidate algorithms are compared and evaluated. The Ulivieri (1985) algorithm is determined to be optimal for the algorithm of FY-4A LST official products. The refined algorithm coefficients for distinguishing dry and moist atmosphere were established for daytime and nighttime, respectively. Then, FY-4A LST official products under clear-sky conditions are produced. The validation results show that: (1) Compared with in-situ measured LST data at the HeBi crop measurement network, the root mean square errors (RMSE) were 2.139 and 2.447 K. Compared with in-situ measured LST data at Naqu alpine meadow site of Tibet plateau, the RMSE was 2.86 K. (2) When compared with the MODIS LST product, the RMSE was 1.64, 2.17, 2.6, and 1.73 K in March, July, October, and December, respectively. By the bias long-time change at a single site, RMSE of the XLHT (city) and GZH (desert) sites were 2.735 and 2.97 K, respectively. Overall, the preferred algorithm exhibits good accuracy and meets the required accuracy of the FY-4A mission.<\/jats:p>","DOI":"10.3390\/rs15092437","type":"journal-article","created":{"date-parts":[[2023,5,8]],"date-time":"2023-05-08T02:03:31Z","timestamp":1683511411000},"page":"2437","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Inversion and Validation of FY-4A Official Land Surface Temperature Product"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7945-9073","authenticated-orcid":false,"given":"Lixin","family":"Dong","sequence":"first","affiliation":[{"name":"Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China"}]},{"given":"Shihao","family":"Tang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing 100081, China"}]},{"given":"Fuzhou","family":"Wang","sequence":"additional","affiliation":[{"name":"Hebi Meteorological Bureau of Henan Province, Hebi 458000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4776-1918","authenticated-orcid":false,"given":"Michael","family":"Cosh","sequence":"additional","affiliation":[{"name":"Hydrology and Remote Sensing Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8688-6206","authenticated-orcid":false,"given":"Xianxiang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University (Zhuhai), Zhuhai 519082, China"},{"name":"Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University (Zhuhai), Zhuhai 519082, China"}]},{"given":"Min","family":"Min","sequence":"additional","affiliation":[{"name":"School of Atmospheric Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University (Zhuhai), Zhuhai 519082, China"},{"name":"Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University (Zhuhai), Zhuhai 519082, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"19567","DOI":"10.1038\/s41598-019-55733-3","article-title":"Assimilating Satellite Land Surface States Data from Fengyun-4A","volume":"9","author":"Meng","year":"2019","journal-title":"Sci. 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