{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T05:24:29Z","timestamp":1779081869817,"version":"3.51.4"},"reference-count":48,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,5,22]],"date-time":"2024-05-22T00:00:00Z","timestamp":1716336000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Natural Science Foundation of Hunan Province-Outstanding Youth Foundation","award":["2023JJ20050"],"award-info":[{"award-number":["2023JJ20050"]}]},{"name":"the Natural Science Foundation of Hunan Province-Outstanding Youth Foundation","award":["U2142209"],"award-info":[{"award-number":["U2142209"]}]},{"name":"the Natural Science Foundation of Hunan Province-Outstanding Youth Foundation","award":["42075011"],"award-info":[{"award-number":["42075011"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2023JJ20050"],"award-info":[{"award-number":["2023JJ20050"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U2142209"],"award-info":[{"award-number":["U2142209"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["42075011"],"award-info":[{"award-number":["42075011"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The integration of high-resolution aerosol measurements into an atmospheric chemistry model can improve air quality forecasting. However, traditional data assimilation methods are challenged in effectively incorporating such detailed aerosol information. This study utilized the WRF-Chem model to conduct data assimilation and prediction experiments using the Himawari-8 satellite\u2019s aerosol optical depth (AOD) product and ground-level particulate matter concentration (PM) measurements during a record-breaking dust event in the Beijing\u2013Tianjin\u2013Hebei region from 14 to 18 March 2021. Three experiments were conducted, comprising a control experiment without assimilation (CTL), a traditional three-dimensional variational (3DVAR) experiment, and a multi-scale three-dimensional variational (MS-3DVAR) experiment. The results indicated that the CTL method significantly underestimated the intensity and extent of the severe dust event, while the analysis fields and forecasting fields of PM concentration and AOD can be significantly improved in both 3DVAR and MS-3DVAR assimilation. Particularly, the MS-3DVAR assimilation approach yielded better-fitting extreme values than the 3DVAR method, mostly likely due to the multi-scale information from the observations used in the MS-3DVAR method. Compared to the CTL method, the correlation coefficient of MS-3DVAR assimilation between the assimilated PM10 analysis fields and observations increased from 0.24 to 0.93, and the positive assimilation effect persisted longer than 36 h. These findings suggest the effectiveness and prolonged influence of integrating high-resolution aerosol observations through MS-3DVAR assimilation in improving aerosol forecasting capabilities.<\/jats:p>","DOI":"10.3390\/rs16111852","type":"journal-article","created":{"date-parts":[[2024,5,22]],"date-time":"2024-05-22T11:03:47Z","timestamp":1716375827000},"page":"1852","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Optimizing the Numerical Simulation of the Dust Event of March 2021: Integrating Aerosol Observations through Multi-Scale 3D Variational Assimilation in the WRF-Chem Model"],"prefix":"10.3390","volume":"16","author":[{"given":"Shuang","family":"Mei","sequence":"first","affiliation":[{"name":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-3783-6989","authenticated-orcid":false,"given":"Wei","family":"You","sequence":"additional","affiliation":[{"name":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Zhong","sequence":"additional","affiliation":[{"name":"College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zengliang","family":"Zang","sequence":"additional","affiliation":[{"name":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianping","family":"Guo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiangyue","family":"Xiang","sequence":"additional","affiliation":[{"name":"College of Meteorology and Oceanography, National University of Defense Technology, Changsha 410073, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,5,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"7905","DOI":"10.5194\/acp-22-7905-2022","article-title":"Record-Breaking Dust Loading during Two Mega Dust Storm Events over Northern China in March 2021: Aerosol Optical and Radiative Properties and Meteorological Drivers","volume":"22","author":"Gui","year":"2022","journal-title":"Atmos. 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