{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T07:18:18Z","timestamp":1768720698910,"version":"3.49.0"},"reference-count":29,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2019,11,29]],"date-time":"2019-11-29T00:00:00Z","timestamp":1574985600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Korea Institute of Civil Engineering and Building Technology","award":["20190149-001"],"award-info":[{"award-number":["20190149-001"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The melting layer (ML) is an important region used to describe the transition of hydrometeors from the solid to the liquid phase. It is a typical feature used to characterize the vertical structure of the stratiform precipitation. The present study implements a new automatic melting-layer detection algorithm based on the range-height-indicator\u2013quasi-vertical profile (R-QVP) in the X-band dual-polarization radars. The algorithm uses the gradients of the polarimetric radar variables reflectivity factor at horizontal polarization (Zh), differential reflectivity (Zdr), and copolar correlation coefficient (\u03c1hv), and their combinations to describe the ML characteristics. The melting layer heights derived from the radar were compared and validated with the heights of the 0 \u00b0C wet-bulb temperature derived from the Modern-Era retrospective analysis for research and applications (MERRA) reanalysis datasets and obtained high correlation coefficient 0.96. The R-QVP combined with this algorithm led to spatial and temporal variabilities of the melting layer thickness. The thickness of the melting layer was independent of the seasonal, spatial, and temporal variabilities of the precipitations. Intriguing polarimetric signatures have been observed inside, above, and below the ML, based on the phase of the precipitation particles. The statistics of the polarimetric variables were evaluated for ML, rain, and snow. Further, the linkage between enhanced specific differential phase shift (Kdp) and Zdr in the dendritic growth layer (DGL) and surface precipitation was also described.<\/jats:p>","DOI":"10.3390\/rs11232848","type":"journal-article","created":{"date-parts":[[2019,12,2]],"date-time":"2019-12-02T10:50:45Z","timestamp":1575283845000},"page":"2848","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Melting Layer Detection and Characterization based on Range Height Indicator\u2013Quasi Vertical Profiles"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0130-1193","authenticated-orcid":false,"given":"Shaik","family":"Allabakash","sequence":"first","affiliation":[{"name":"Korea Institute of Civil Engineering and Building Technology, Ilsan 10223, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0545-9369","authenticated-orcid":false,"given":"Sanghun","family":"Lim","sequence":"additional","affiliation":[{"name":"Korea Institute of Civil Engineering and Building Technology, Ilsan 10223, Korea"}]},{"given":"Bong-Joo","family":"Jang","sequence":"additional","affiliation":[{"name":"Korea Institute of Civil Engineering and Building Technology, Ilsan 10223, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1354","DOI":"10.1175\/2007JAMC1634.1","article-title":"Automatic designation of the melting layer with a polarimetric prototype of the WSR-88D radar","volume":"47","author":"Giangrande","year":"2008","journal-title":"J. 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