Understanding the microphysical control and spatial-temporal variability of warm rain probability using CloudSat and MODIS observations

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dc.contributor.authorZhang, Zhibo
dc.contributor.authorOreopoulos, Lazaros
dc.contributor.authorLebsock, Matthew D.
dc.contributor.authorMechem, David B.
dc.contributor.authorCovert, Justin
dc.date.accessioned2022-06-24T17:39:13Z
dc.date.available2022-06-24T17:39:13Z
dc.date.issued2022-05-13
dc.description.abstractBy combining measurements from MODIS and the CloudSat radar, we develop a parameterization scheme to quantify the combined microphysical controls by liquid water path (LWP) and cloud droplet number concentration (CDNC) of the probability of precipitation (PoP) in marine low cloud over tropical oceans. We demonstrate that the spatial-temporal variation of grid-mean in-cloud <PoP> can be largely explained by the variation of the joint probability density function of LWP and CDNC in the phase space specified by the bivariate PoP (LWP and CDNC) function. Through a series of sensitivity tests guided by this understanding, we find that in the Southeastern Pacific and Atlantic the stratocumulus to cumulus transition of the <PoP> is mainly due to the variation of CDNC while the annual cycle is mainly due to the variation of LWP. The results of this study provide a viable way to diagnose the root cause of warm rain problems in global climate models.en_US
dc.description.sponsorshipZ. Zhang acknowledges the financial support from the Atmospheric System Research (Grant DE-SC0020057) funded by the Office of Biological and Environmental Research in the US Department of Energy Office of Science. L. Oreopoulos and Z. Zhang acknowledge funding by NASA's CCST program. The research by M. D. Lebsock was carried out at the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA, under contract with the National Aeronautics and Space Administration. Coauthor D. Mechem was supported by subcontract OFED0010-01 from the University of Maryland Baltimore County and the U.S. Department of Energy's Atmospheric Systems Research Grant No. DE-SC0016522. The computations in this study were performed at the UMBC High Performance Computing Facility. The facility is supported by the U.S. National Science Foundation through the MRI program (Grants CNS-0821258 and CNS-1228778) and the SCREMS program (Grant DMS-0821311), with substantial support from UMBC.en_US
dc.description.urihttps://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2022GL098863en_US
dc.format.extent9 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2mnhz-wd4n
dc.identifier.citationZhang, Z., Oreopoulos, L., Lebsock, M. D., Mechem, D. B., & Covert, J. (2022). Understanding the microphysical control and spatial-temporal variability of warm rain probability using CloudSat and MODIS observations. Geophysical Research Letters, 49, e2022GL098863.https://doi.org/10.1029/2022GL098863en_US
dc.identifier.urihttps://doi.org/10.1029/2022GL098863
dc.identifier.urihttp://hdl.handle.net/11603/25038
dc.language.isoen_USen_US
dc.publisherAGUen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Physics Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC GESTAR II
dc.rightsThis work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.en_US
dc.rightsPublic Domain Mark 1.0*
dc.rights.urihttp://creativecommons.org/publicdomain/mark/1.0/*
dc.titleUnderstanding the microphysical control and spatial-temporal variability of warm rain probability using CloudSat and MODIS observationsen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0001-9491-1654en_US

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