{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T07:26:00Z","timestamp":1768721160051,"version":"3.49.0"},"reference-count":69,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,5,13]],"date-time":"2021-05-13T00:00:00Z","timestamp":1620864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Wet snow may cause significant damage to humans and property, and thus, it is necessary to estimate the corresponding liquid fraction (FL). Consequently, the FL of wet snow was estimated using a novel technique; specifically, the particle shape irregularity (Ir) was estimated through the particle coordinate information obtained using 2-D video disdrometer (2DVD) measurements. Moreover, the possibility of quantitively estimating FL via Ir, based on the temperature (T), was examined. Eight snowfall cases from 2014 to 2016 were observed through a 2DVD installed in Jincheon, South Korea, to analyze the dominant properties of physical variables of snowflakes (i.e., the terminal velocity (VT), particle density (\u03c1s), Ir, and FL) and the corresponding relationships according to the T ranges (\u22124.5 &lt; T (\u00b0C) &lt; 2.5) in which wet snow can occur. It was clarified that the volume-equivalent particle diameter (D)\u2013FL and D\u2013Ir relationships depended on T, and a relationship existed between Ir and FL. The analysis results were verified using the Yong-In Testbed (YIT) S-band weather radar and T-matrix scattering simulation. The D\u2013FL relationship was implemented in the scattering simulation, and the results indicated that the simulated reflectivity (ZS) was highly correlated with the observed reflectivity (ZO) under all T classes. These features can provide a basis for radar analysis and quantitative snowfall estimation for wet snow with various FL values.<\/jats:p>","DOI":"10.3390\/rs13101901","type":"journal-article","created":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T03:28:36Z","timestamp":1620962916000},"page":"1901","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Estimation of Liquid Fraction of Wet Snow by Using 2-D Video Disdrometer and S-Band Weather Radar"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1974-2990","authenticated-orcid":false,"given":"Sung-Ho","family":"Suh","sequence":"first","affiliation":[{"name":"Flight Safety Technology Division, NARO Space Center, Korea Aerospace Research Institute (KARI), Goheung-gun 59571, Korea"},{"name":"Atmospheric Environmental Research Institute (AERI), Pukyong National University (PKNU), Busan 48513, Korea"}]},{"given":"Hong-Il","family":"Kim","sequence":"additional","affiliation":[{"name":"Flight Safety Technology Division, NARO Space Center, Korea Aerospace Research Institute (KARI), Goheung-gun 59571, Korea"}]},{"given":"Eun-Ho","family":"Choi","sequence":"additional","affiliation":[{"name":"Flight Safety Technology Division, NARO Space Center, Korea Aerospace Research Institute (KARI), Goheung-gun 59571, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7308-241X","authenticated-orcid":false,"given":"Cheol-Hwan","family":"You","sequence":"additional","affiliation":[{"name":"Atmospheric Environmental Research Institute (AERI), Pukyong National University (PKNU), Busan 48513, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/0169-8095(94)00004-W","article-title":"Some characteristics of the precipitation formed within winter storms over eastern Newfoundland","volume":"36","author":"Stewart","year":"1995","journal-title":"Atmos. 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