Climatology of Melting Layer Heights Estimated From Cloud Radar Observations at Various Locations. Issue 17 (30th August 2021)

• Record Type: Journal Article
• Authors: Song, Jae In; Yum, Seong Soo; Park, Sung‐Hwa; Kim, Ki‐Hoon; Park, Ki‐Jun; Joo, Sang‐Won
• Is Part Of: Journal of geophysical research. Volume 126:Issue 17(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-08-30
• Subjects: cloud radar -- melting layer -- cloud climatology; Atmospheric physics -- Periodicals; Geophysics -- Periodicals; 551.5
• DOI: 10.1029/2021JD034816
• Languages: English
• ISSNs: 2169-897X

Abstract

Abstract: A melting layer (ML) detection algorithm for cloud radar with polarimetric capability was developed and applied to the cloud radar data collected from five different sites around the world for several years. The retrieved melting layer top height (MLH) showed a very good correspondence with the ECMWF Reanalysis 5 zero degree level data for all five sites. The ML characteristics were distinctively different for different sites, revealing climatological characteristics of ML forming clouds in different regions. Generally, ML tended to occur more frequently in summer than in winter except for a maritime site, where low stratiform clouds formed frequently in summer, the top of which might be lower than the freezing level. In contrast, at two Arctic sites, ML occurred almost exclusively in summer because it was too cold to have an ML in the other seasons. The MLH also varied significantly from site to site but generally was higher during warmer seasons. Based on MLH, two new indices, bulk temperature lapse rate (BLR) and relative depth (RD) of liquid cloud below MLH (RD) were developed, which were useful to explain the environmental characteristics of the five sites. BLR generally increased with the surface temperature at all sites except at the marine site that showed an opposite trend, where a unique synoptic pattern in winter generated high BLR in this cold season. These findings confirm that studies on thermodynamic structures using cloud radars can be broadened, taking advantage of BLR and RD information, as these indices can represent environmental thermodynamic characteristics of the clouds that have ML. Key Points: A melting layer detection algorithm for Ka‐band cloud radar is developed and shows good agreement with the reanalysis data The occurrence frequency and the height of the melting layer at five different sites exhibit different environmental characteristics Two newly introduced indices well represent the thermodynamic characteristics of clouds that have a melting layer