{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T00:24:03Z","timestamp":1773966243706,"version":"3.50.1"},"reference-count":25,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,24]],"date-time":"2021-04-24T00:00:00Z","timestamp":1619222400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1852977"],"award-info":[{"award-number":["1852977"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>A melting layer detection algorithm is developed for the NCAR 94 GHz airborne cloud radar (HIAPER CloudRadar, HCR). The detection method is based on maxima in the linear depolarization ratio and a discontinuity in the radial velocity field. A melting layer field is added to the radar data, which provides detected, interpolated, and estimated altitudes of the melting layer and the altitude of the 0 \u00b0C isotherm detected in model temperature data. The icing level is defined as the lowest melting layer, and the cloud data are flagged as either above (cold) or below (warm) the icing level. Analysis of the detected melting layer shows that the offset between the 0 \u00b0C isotherm and the actual melting layer varies with cloud type: in heavy convection sampled in the tropics, the melting layer is found up to 500 m below the 0 \u00b0C isotherm, while in shallow clouds, the offset is much smaller or sometimes vanishes completely. A relationship between the offset and the particle fall speed both above and below the melting layer is established. Special phenomena, such as a lowering of the melting layer towards the center of storms or split melting layers, were observed.<\/jats:p>","DOI":"10.3390\/rs13091660","type":"journal-article","created":{"date-parts":[[2021,4,25]],"date-time":"2021-04-25T02:12:57Z","timestamp":1619316777000},"page":"1660","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Melting Layer Detection and Observation with the NCAR Airborne W-Band Radar"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7816-0942","authenticated-orcid":false,"given":"Ulrike","family":"Romatschke","sequence":"first","affiliation":[{"name":"Earth Observing Laboratory, National Center for Atmospheric Research (NCAR), Boulder, CO 80301, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"161","DOI":"10.5194\/gi-4-161-2015","article-title":"A Wing Pod-Based Millimeter Wavelength Airborne Cloud Radar","volume":"4","author":"Vivekanandan","year":"2015","journal-title":"Geosci. Instrum. Methods Data Syst."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Romatschke, U., Dixon, M., Tsai, P., Loew, E., Vivekanandan, J., Emmett, J., and Rilling, R. (2021). The NCAR Airborne 94-GHz Cloud Radar: Calibration and Data Processing. arXiv.","DOI":"10.31223\/X55894"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1541","DOI":"10.1175\/JAM2155.1","article-title":"Freezing-Level Estimation with Polarimetric Radar","volume":"43","author":"Brandes","year":"2004","journal-title":"J. Appl. Meteorol. Climatol."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Lee, J.-E., Jung, S.-H., and Kwon, S. (2020). Characteristics of the Bright Band Based on Quasi-Vertical Profiles of Polarimetric Observations from an S-Band Weather Radar Network. Remote Sens., 12.","DOI":"10.3390\/rs12244061"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2873","DOI":"10.5194\/amt-14-2873-2021","article-title":"Detection of the Melting Level with Polarimetric Weather Radar","volume":"14","year":"2021","journal-title":"Atmos. Meas. Tech."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2723","DOI":"10.1175\/JHM-D-17-0005.1","article-title":"The Chilean Coastal Orographic Precipitation Experiment: Observing the Influence of Microphysical Rain Regimes on Coastal Orographic Precipitation","volume":"18","author":"Massmann","year":"2017","journal-title":"J. Hydrometeorol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1887","DOI":"10.1175\/JTECH-D-16-0016.1","article-title":"Rain Type Classification Algorithm Module for GPM Dual-Frequency Precipitation Radar","volume":"33","author":"Awaka","year":"2016","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_8","unstructured":"Haynes, J.M. (2021, April 21). CloudSat 2C-PRECIP-COLUMN Data Product Process Description and Interface Control Document. Available online: http:\/\/www.cloudsat.cira.colostate.edu\/sites\/default\/files\/products\/files\/2C-PRECIP-COLUMN_PDICD.P1_R05.rev1_pdf."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3648","DOI":"10.1109\/TGRS.2012.2224352","article-title":"Hydrometeor Profile Characterization Method for Dual-Frequency Precipitation Radar Onboard the GPM","volume":"51","author":"Le","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1175\/BAMS-D-17-0180.1","article-title":"Cloud System Evolution in the Trades\u2014CSET","volume":"100","author":"Albrecht","year":"2019","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_11","unstructured":"NCAR\/EOL Remote Sensing Facility (2021). CSET: NCAR HCR Radar Moments Data. Version 2.1, UCAR\/NCAR-Earth Observing Laboratory."},{"key":"ref_12","first-page":"1","article-title":"Observations of Clouds, Aerosols, Precipitation, and Surface Radiation over the Southern Ocean: An Overview of CAPRICORN, MARCUS, MICRE and SOCRATES","volume":"1","author":"McFarquhar","year":"2020","journal-title":"Bull. Am. Meteorol. Soc."},{"key":"ref_13","unstructured":"NCAR\/EOL Remote Sensing Facility (2021). SOCRATES: NCAR HCR Radar Moments Data. Version 2.1, UCAR\/NCAR-Earth Observing Laboratory."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e2020GL087564","DOI":"10.1029\/2020GL087564","article-title":"OTREC2019: Convection Over the East Pacific and Southwest Caribbean","volume":"47","author":"Raymond","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_15","unstructured":"NCAR\/EOL Remote Sensing Facility (2021). OTREC: NCAR HCR Radar Moments Data. Version 2.2, UCAR\/NCAR-Earth Observing Laboratory."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Allabakash, S., Lim, S., and Jang, B.-J. (2019). Melting Layer Detection and Characterization Based on Range Height Indicator\u2013Quasi Vertical Profiles. Remote Sens., 11.","DOI":"10.3390\/rs11232848"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1345","DOI":"10.1175\/1520-0426(2001)018<1345:ROAAUC>2.0.CO;2","article-title":"Retrieval of Atmospheric Attenuation Using Combined Ground-Based and Airborne 95-GHz Cloud Radar Measurements","volume":"18","author":"Li","year":"2001","journal-title":"J. Atmospheric Ocean. Technol."},{"key":"ref_18","unstructured":"UCAR\/NCAR-Earth Observing Laboratory (2016). NSF\/NCAR GV (HIAPER) QC Dropsonde Data. Version 4.0, UCAR\/NCAR-Earth Observing Laboratory."},{"key":"ref_19","unstructured":"UCAR\/NCAR-Earth Observing Laboratory, and Voemel, H. (2018). NCAR\/EOL Quality Controlled Dropsonde Data. Version 1.1, UCAR\/NCAR-Earth Observing Laboratory."},{"key":"ref_20","unstructured":"UCAR\/NCAR-Earth Observing Laboratory, and Voemel, H. (2019). NCAR\/EOL AVAPS Dropsonde QC Data. Version 1.0, UCAR\/NCAR-Earth Observing Laboratory."},{"key":"ref_21","first-page":"1107","article-title":"High-Resolution in Situ Observations of Atmospheric Thermodynamics Using Dropsondes during the Organization of Tropical East Pacific Convection (OTREC) Field Campaign","volume":"17","author":"Goodstein","year":"2021","journal-title":"Earth Syst. Sci. Data Discuss."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"e2020GL087499","DOI":"10.1029\/2020GL087499","article-title":"Two Layers of Melting Ice Particles Within a Single Radar Bright Band: Interpretation and Implications","volume":"47","author":"Li","year":"2020","journal-title":"Geophys. Res. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1590","DOI":"10.1080\/01621459.2012.737745","article-title":"Optimal Detection of Changepoints With a Linear Computational Cost","volume":"107","author":"Killick","year":"2012","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_24","unstructured":"(2021, March 09). American Meteorological Society Icing Level-Glossary of Meteorology. Available online: https:\/\/glossary.ametsoc.org\/wiki\/Icing_level."},{"key":"ref_25","unstructured":"Trujillo-Ortiz, A. (2018, March 18). Gmregress. MATLAB Central File Exchange 2018, Available online: https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/27918-gmregress."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1660\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:52:15Z","timestamp":1760161935000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1660"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,24]]},"references-count":25,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13091660"],"URL":"https:\/\/doi.org\/10.3390\/rs13091660","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,24]]}}}