Simplified ISCCP cloud regimes for evaluating cloudiness in CMIP5 models

dc.contributor.authorJin, Daeho
dc.contributor.authorOreopoulos, Lazaros
dc.contributor.authorLee, Dongmin
dc.date.accessioned2025-09-18T14:22:03Z
dc.date.issued2017-04-15
dc.description.abstractWe take advantage of ISCCP simulator data available for many models that participated in CMIP5, in order to introduce a framework for comparing model cloud output with corresponding ISCCP observations based on the cloud regime (CR) concept. Simplified global CRs are employed derived from the co-variations of three variables, namely cloud optical thickness, cloud top pressure and cloud fraction (τ, p*, CF). Following evaluation criteria established in a companion paper of ours (Jin et al. 2016), we assess model cloud simulation performance based on how well the simplified CRs are simulated in terms of similarity of centroids, global values and map correlations of relative-frequency-of-occurrence, and long-term total cloud amounts. Mirroring prior results, modeled clouds tend to be too optically thick and not as extensive as in observations. CRs with high-altitude clouds from storm activity are not as well simulated here compared to the previous study, but other regimes containing near-overcast low clouds show improvement. Models that have performed well in the companion paper against CRs defined by joint τ-p* pchistograms distinguish themselves again here, but improvements for previously underperforming models are also seen. Averaging across models does not yield a drastically better picture, except for cloud geographical locations. Cloud evaluation with simplified regimes seems thus more forgiving than that using histogram-based CRs while still strict enough to reveal model weaknesses. *= subscript c
dc.description.sponsorshipWe acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. Lastly, funding by NASA’s Modeling Analysis and Prediction (MAP) program is gratefully acknowledged
dc.description.urihttps://link.springer.com/article/10.1007/s00382-016-3107-6
dc.format.extent18 pages
dc.genrejournal articles
dc.identifierdoi:10.13016/m23tvw-kiei
dc.identifier.citationJin, Daeho, Lazaros Oreopoulos, and Dongmin Lee. “Simplified ISCCP Cloud Regimes for Evaluating Cloudiness in CMIP5 Models.” Climate Dynamics 48, no. 1 (2017): 113–30. https://doi.org/10.1007/s00382-016-3107-6.
dc.identifier.urihttps://doi.org/10.1007/s00382-016-3107-6
dc.identifier.urihttp://hdl.handle.net/11603/40174
dc.language.isoen
dc.publisherSpringer Nature
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
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.
dc.rightsPublic Domain
dc.rights.urihttps://creativecommons.org/publicdomain/mark/1.0/
dc.subjectCMIP5 evaluation
dc.subjectCloud assessment
dc.subjectCOSP
dc.subjectCloud regime
dc.subjectCFMIP
dc.subjectISCCP simulator
dc.subjectCloud climatology
dc.titleSimplified ISCCP cloud regimes for evaluating cloudiness in CMIP5 models
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0003-4389-4393

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