{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:40:01Z","timestamp":1760233201837,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,22]],"date-time":"2022-12-22T00:00:00Z","timestamp":1671667200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["42275175","42275056","41801022","8192016"],"award-info":[{"award-number":["42275175","42275056","41801022","8192016"]}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["42275175","42275056","41801022","8192016"],"award-info":[{"award-number":["42275175","42275056","41801022","8192016"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Based on the Beijing Climate Center\u2019s land surface model BCC_AVIM2.0, an ensemble Kalman filter (EnKF) algorithm is developed to assimilate the land surface temperature (LST) product of the first satellite of Fengyun-4 series meteorological satellites of China to study the influence of LST data with different time frequencies on the surface temperature data assimilations. The MODIS daytime and nighttime LST products derived from Terra and Aqua satellites are used as independent validation data to test the assimilation results. The results show that diurnal variation information in the FY-4A LST data has significant effect on the assimilation results. When the time frequencies of the assimilated FY-4A LST data are sufficient, the assimilation scheme can effectively reduce the errors and the assimilation results reflect more reasonable spatial and temporal distributions. The assimilation experiments with a 3 h time frequency show less bias as well as RMSEs and higher temporal correlations than that of the model simulations at both daytime and nighttime periods. As the temporal frequency of assimilated LST observations decreases, the assimilation effects gradually deteriorate. When diurnal variation information is not considered at all in the assimilation, the assimilation with 24 h time frequency showed the largest errors and smallest time correlations in all experiments. The results demonstrate the potential of assimilating high-frequency FY-4A LST data to improve the performance of the BCC_AVIM2.0 land surface model. Furthermore, this study indicates that the diurnal variation information is a necessary factor needed to be considered when assimilating the FY-4A LST.<\/jats:p>","DOI":"10.3390\/rs15010059","type":"journal-article","created":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T03:26:25Z","timestamp":1671765985000},"page":"59","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["The Influence of FY-4A High-Frequency LST Data on Data Assimilation in a Climate Model"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8405-1125","authenticated-orcid":false,"given":"Suping","family":"Nie","sequence":"first","affiliation":[{"name":"Earth System Modeling and Prediction Centre, China Meteorological Administration, Beijing 100081, China"},{"name":"State Key Laboratory of Severe Weather, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaolong","family":"Jia","sequence":"additional","affiliation":[{"name":"National Climate Center, China Meteorological Administration, Beijing 100081, China"},{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weitao","family":"Deng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)\/Joint International Research Laboratory of Climate and Environment Change (ILCEC)\/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science and Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9823-9367","authenticated-orcid":false,"given":"Yixiong","family":"Lu","sequence":"additional","affiliation":[{"name":"Earth System Modeling and Prediction Centre, China Meteorological Administration, Beijing 100081, China"},{"name":"State Key Laboratory of Severe Weather, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongyan","family":"He","sequence":"additional","affiliation":[{"name":"Anhui Climate Center, Hefei 230031, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4388-526X","authenticated-orcid":false,"given":"Liang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weihua","family":"Cao","sequence":"additional","affiliation":[{"name":"Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueliang","family":"Deng","sequence":"additional","affiliation":[{"name":"Hefei Meteorological Bureau, Hefei 230031, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1007\/BF00865986","article-title":"Infrared measurement of canopy temperature and detection of plant water stress","volume":"42","author":"Fuchs","year":"1990","journal-title":"Theor. 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