{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T23:25:04Z","timestamp":1773444304995,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2022,7,19]],"date-time":"2022-07-19T00:00:00Z","timestamp":1658188800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000015","name":"U.S. Department of Energy Office of Science (BER)","doi-asserted-by":"publisher","award":["DE-SC0020135"],"award-info":[{"award-number":["DE-SC0020135"]}],"id":[{"id":"10.13039\/100000015","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The ice cloud detection sensitivity of the millimeter cloud radar (MMCR) and the Ka-band Zenith radar (KAZR) is investigated using a collocated Raman lidar (RL) at the Atmospheric Radiation Measurement Program Southern Great Plains site. Only profiles that are transparent to the RL with ice clouds only are considered in this study. The MMCR underestimates the RL ice cloud optical depth (COD) by 20%. The MMCR detects no ice clouds in 37% of the profiles. These profiles where ice cloud goes undetected by the MMCR typically contain very optically thin clouds, with a mean RL ice COD of 0.03. Higher ice cloud detection sensitivity is found for the KAZR, which underestimates the RL ice COD by 15%. The decrease in the ice COD bias for the KAZR compared to the MMCR is largely due to a decrease in the ice COD bias for the situation where the transparent profiles with ice clouds are detected by both the RL and cloud radar. The climatic net ice cloud radiative effects (CREs) from the RL at the top of the atmosphere (TOA) and the surface are 3.2 W m\u22122 and \u22120.6 W m\u22122, respectively. The ice CREs at the TOA and surface are underestimated for the MMCR by 0.7 W m\u22122 and 0.16 W m\u22122 (21% and 29%) and underestimated for the KAZR by 0.6 W m\u22122 and 0.14 W m\u22122 (17% and 24%). The ice clouds undetected by the cloud radars led to underestimating the climatic net cloud heating rates below 150 hPa by about 0\u20130.04 K day\u22121.<\/jats:p>","DOI":"10.3390\/rs14143466","type":"journal-article","created":{"date-parts":[[2022,7,19]],"date-time":"2022-07-19T23:10:22Z","timestamp":1658272222000},"page":"3466","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["An Investigation of the Ice Cloud Detection Sensitivity of Cloud Radars Using the Raman Lidar at the ARM SGP Site"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8820-2111","authenticated-orcid":false,"given":"Mingcheng","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195, USA"}]},{"given":"Kelly A.","family":"Balmes","sequence":"additional","affiliation":[{"name":"Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO 80303, USA"},{"name":"NOAA Global Monitoring Laboratory, Boulder, CO 80305, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4405-3572","authenticated-orcid":false,"given":"Tyler J.","family":"Thorsen","sequence":"additional","affiliation":[{"name":"NASA Langley Research Center, Hampton, VA 23681, USA"}]},{"given":"Dylan","family":"Willick","sequence":"additional","affiliation":[{"name":"Carleton College, Northfield, MN 55057, USA"}]},{"given":"Qiang","family":"Fu","sequence":"additional","affiliation":[{"name":"Department of Atmospheric Sciences, University of Washington, Seattle, WA 98195, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9492","DOI":"10.1002\/2014JD021458","article-title":"Cloud properties and radiative effects of the Asian summer monsoon derived from A\u2014Train data","volume":"119","author":"Berry","year":"2014","journal-title":"J. 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