{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:05:09Z","timestamp":1760231109187,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2022,8,26]],"date-time":"2022-08-26T00:00:00Z","timestamp":1661472000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41930972","42175008","42192554","2021KJ031","2015CB452804","2021LASW-A12","2022LASW-B08"],"award-info":[{"award-number":["41930972","42175008","42192554","2021KJ031","2015CB452804","2021LASW-A12","2022LASW-B08"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"S&amp;T Development Fund of CAMS","award":["41930972","42175008","42192554","2021KJ031","2015CB452804","2021LASW-A12","2022LASW-B08"],"award-info":[{"award-number":["41930972","42175008","42192554","2021KJ031","2015CB452804","2021LASW-A12","2022LASW-B08"]}]},{"name":"National Basic Research Program of China","award":["41930972","42175008","42192554","2021KJ031","2015CB452804","2021LASW-A12","2022LASW-B08"],"award-info":[{"award-number":["41930972","42175008","42192554","2021KJ031","2015CB452804","2021LASW-A12","2022LASW-B08"]}]},{"name":"Open Grants of the State Key Laboratory of Severe Weather","award":["41930972","42175008","42192554","2021KJ031","2015CB452804","2021LASW-A12","2022LASW-B08"],"award-info":[{"award-number":["41930972","42175008","42192554","2021KJ031","2015CB452804","2021LASW-A12","2022LASW-B08"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Extreme rainfall induced by landfalling typhoon (ERLTC) can cause destructive natural disasters throughout China. Cloud properties in ERLTC are not yet well understood and parameterized, which limits the forecast accuracy of ERLTC to some extent. The 99th percentile intensity of daily rainfall associated with LTC is objectively defined as ERLTC and using the CloudSat tropical cyclone (CSTC) dataset from 2006 to 2018, cloud macro- and microphysical characteristics are statistically investigated. Results show that the proportion of single-layer (double-layered) clouds increases (decreases) significantly on the occurrence day of ERLTC. In the TC inner core region, the proportion of deep convective cloud at 2\u201310 km is the highest, reaching 50%. In the TC envelop region, deep convective cloud at the height of 3\u20138 km and cirrus at the height of 12\u201314 km account for the highest proportions. For the TC outer region, cirrus around 13 km has the highest proportion. During the ERLTC period, the ice-water content is mainly distributed in 5\u201318 km, and is mostly distributed in the TC inner core, followed by the envelop region. A large number of smaller ice particles are gathering in the upper troposphere at 13\u201318 km, while a small number of larger ones is gathering in the middle levels around 8\u201310 km. These results are useful for evaluating the ERLTC simulations and are expected to provide new forecasting factors for ERLTC in cloud macro- and microphysical perspectives.<\/jats:p>","DOI":"10.3390\/rs14174200","type":"journal-article","created":{"date-parts":[[2022,8,30]],"date-time":"2022-08-30T01:37:55Z","timestamp":1661823475000},"page":"4200","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Cloud Macro- and Microphysical Properties in Extreme Rainfall Induced by Landfalling Typhoons over China"],"prefix":"10.3390","volume":"14","author":[{"given":"Dajun","family":"Zhao","sequence":"first","affiliation":[{"name":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China"}]},{"given":"Yubin","family":"Yu","sequence":"additional","affiliation":[{"name":"China Meteorological Administration Training Centre, China Meteorological Administration, Beijing 100081, China"}]},{"given":"Ying","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China"}]},{"given":"Hongxiong","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China"}]},{"given":"Lianshou","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1195","DOI":"10.1175\/BAMS-87-9-1195","article-title":"The Dvorak Tropical Cyclone Intensity Estimation Technique: A Satellite-Based Method that Has Endured for over 30 Years","volume":"87","author":"Velden","year":"2006","journal-title":"Bull. 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