{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T11:56:00Z","timestamp":1768996560747,"version":"3.49.0"},"reference-count":51,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,11,29]],"date-time":"2022-11-29T00:00:00Z","timestamp":1669680000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Chinese National Natural Science Foundation of China","award":["G42192553"],"award-info":[{"award-number":["G42192553"]}]},{"name":"the Chinese National Natural Science Foundation of China","award":["G41805016"],"award-info":[{"award-number":["G41805016"]}]},{"name":"the Chinese National Natural Science Foundation of China","award":["G41805070"],"award-info":[{"award-number":["G41805070"]}]},{"name":"the Chinese National Natural Science Foundation of China","award":["21XD1404500"],"award-info":[{"award-number":["21XD1404500"]}]},{"name":"the Chinese National Natural Science Foundation of China","award":["TFJJ202107"],"award-info":[{"award-number":["TFJJ202107"]}]},{"DOI":"10.13039\/501100012247","name":"Program of Shanghai Academic\/Technology Research Leader","doi-asserted-by":"publisher","award":["G42192553"],"award-info":[{"award-number":["G42192553"]}],"id":[{"id":"10.13039\/501100012247","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012247","name":"Program of Shanghai Academic\/Technology Research Leader","doi-asserted-by":"publisher","award":["G41805016"],"award-info":[{"award-number":["G41805016"]}],"id":[{"id":"10.13039\/501100012247","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012247","name":"Program of Shanghai Academic\/Technology Research Leader","doi-asserted-by":"publisher","award":["G41805070"],"award-info":[{"award-number":["G41805070"]}],"id":[{"id":"10.13039\/501100012247","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012247","name":"Program of Shanghai Academic\/Technology Research Leader","doi-asserted-by":"publisher","award":["21XD1404500"],"award-info":[{"award-number":["21XD1404500"]}],"id":[{"id":"10.13039\/501100012247","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012247","name":"Program of Shanghai Academic\/Technology Research Leader","doi-asserted-by":"publisher","award":["TFJJ202107"],"award-info":[{"award-number":["TFJJ202107"]}],"id":[{"id":"10.13039\/501100012247","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shanghai Typhoon Research Foundation","award":["G42192553"],"award-info":[{"award-number":["G42192553"]}]},{"name":"Shanghai Typhoon Research Foundation","award":["G41805016"],"award-info":[{"award-number":["G41805016"]}]},{"name":"Shanghai Typhoon Research Foundation","award":["G41805070"],"award-info":[{"award-number":["G41805070"]}]},{"name":"Shanghai Typhoon Research Foundation","award":["21XD1404500"],"award-info":[{"award-number":["21XD1404500"]}]},{"name":"Shanghai Typhoon Research Foundation","award":["TFJJ202107"],"award-info":[{"award-number":["TFJJ202107"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The module for assimilating radiance data of the Microwave Humidity Sounder-2 (MWHS-2) onboard the Feng Yun 3D (FY-3D) satellite is built in the Weather Research and Forecasting (WRF) model data assimilation (WRFDA) system. The CONV, 3DVar, and EnVar experiments are conducted to investigate the impact of assimilating the new humidity sounder based on Typhoon Ampil (2018). Both the 3DVar and EnVar experiments assimilate FY-3D MWHS-2 radiance data on top of the conventional data, while the CONV experiment only applies conventional data. In the EnVar experiment, notable geopotential height increment is observed around the typhoon, leading the typhoon to move northeast. In addition, the moisture field is improved to some extent. Finally, from the analysis of the dynamic field of the typhoon, it can be found that the EnVar experiment can adjust the dynamic structure of the typhoon. Furthermore, the assimilation of FY-3D MWHS-2 radiance data reduces the forecast error of the typhoon track and intensity. Additionally, the precipitation skill is improved in terms of rainfall pattern and the verification score. This improvement in the precipitation may be closely related to the features of the circulation structure concerning the evolution of the typhoon. The improved prediction of the position and intensity of rainbands in the FY-3D MWHS-2 radiance data assimilation experiment corresponds to a better prediction of typhoon structure.<\/jats:p>","DOI":"10.3390\/rs14236037","type":"journal-article","created":{"date-parts":[[2022,11,30]],"date-time":"2022-11-30T05:45:22Z","timestamp":1669787122000},"page":"6037","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Impacts of 3DEnVar-Based FY-3D MWHS-2 Radiance Assimilation on Numerical Simulations of Landfalling Typhoon Ampil (2018)"],"prefix":"10.3390","volume":"14","author":[{"given":"Lixin","family":"Song","sequence":"first","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 & Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feifei","family":"Shen","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 & Technology, Nanjing 210044, China"},{"name":"Shanghai Typhoon Institute, China Meteorological Administration, Shanghai 200030, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Changliang","family":"Shao","sequence":"additional","affiliation":[{"name":"China Meteorological Administration Meteorological Observation Center, Beijing 100086, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aiqing","family":"Shu","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 & Technology, Nanjing 210044, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lijian","family":"Zhu","sequence":"additional","affiliation":[{"name":"Shanghai Typhoon Institute, China Meteorological Administration, Shanghai 200030, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1175\/1520-0493(2001)129<0420:ASWTET>2.0.CO;2","article-title":"Adaptive sampling with the ensemble transform Kalman filter. 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