{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T11:03:05Z","timestamp":1769252585065,"version":"3.49.0"},"reference-count":38,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:00:00Z","timestamp":1693526400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["42192553"],"award-info":[{"award-number":["42192553"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Ground-based microwave radiometer (GMWR) data with high spatial and temporal resolution can improve the accuracy of weather forecasts when effectively assimilated into numerical weather prediction. Nowadays, the major method to assimilate these data is via indirect assimilation by assimilating the retrieved profiles, which introduces large retrieval errors and cannot easily be represented by an error covariance matrix. Direct assimilation, on the other hand, can avoid this issue. In this study, the ground-based version of the Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV-gb) was selected as the observation operator, and a direct assimilation module for GMWR radiance data was established in the Weather Research and Forecasting Model Data Assimilation (WRFDA). Then, this direct assimilation module was applied to assimilate GMWR data. The results were compared to the indirect assimilation experiment and demonstrated that direct assimilation can more effectively improve the model\u2019s initial fields in terms of temperature and humidity than indirect assimilation while avoiding the influence of retrieval errors. In addition, direct assimilation performed better in the precipitation forecast than indirect assimilation, making the main precipitation center closer to the observation. In particular, the improvement in the precipitation forecast with a threshold of 60 mm\/6 h was obvious, and the corresponding TS score was significantly enhanced.<\/jats:p>","DOI":"10.3390\/rs15174314","type":"journal-article","created":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T08:45:31Z","timestamp":1693557931000},"page":"4314","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Direct Assimilation of Ground-Based Microwave Radiometer Clear-Sky Radiance Data and Its Impact on the Forecast of Heavy Rainfall"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6341-024X","authenticated-orcid":false,"given":"Yujie","family":"Cao","sequence":"first","affiliation":[{"name":"Laboratory of Meteorological Disaster, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Ministry of Education (KLME), Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"given":"Bingying","family":"Shi","sequence":"additional","affiliation":[{"name":"Laboratory of Meteorological Disaster, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Ministry of Education (KLME), Nanjing University of Information Science and Technology, Nanjing 210044, China"}]},{"given":"Xinyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"CMA Institute for Development and Programmer Design, Beijing 100081, China"}]},{"given":"Ting","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Agrometeorological Support and Application Technology of Henan Province, CMA, Zhengzhou 450003, China"},{"name":"Henan Climate Center, Zhengzhou 450003, China"}]},{"given":"Jinzhong","family":"Min","sequence":"additional","affiliation":[{"name":"Laboratory of Meteorological Disaster, Joint International Research Laboratory of Climate and Environment Change (ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Ministry of Education (KLME), Nanjing University of Information Science and Technology, Nanjing 210044, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,9,1]]},"reference":[{"key":"ref_1","unstructured":"Anderson, E. 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