We 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, pc, 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 longterm 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–pc histograms distinguish themselves again here, but improvements for previously underperforming models are also seen. Averaging across models does not yield Electronic supplementary material The online version of this 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.
Simplified ISCCP cloud regimes for evaluating cloudiness in CMIP5 models Daeho Jin1,2 · Lazaros Oreopoulos2 · Dongmin Lee2,3
Jin, D., L. Oreopoulos, and D. Lee (2017), Simplified ISCCP cloud regimes for evaluating cloudiness in CMIP5 models Daeho Jin1,2 · Lazaros Oreopoulos2 · Dongmin Lee2,3 , Clim. Dyn., 48, 113-130, doi:10.1007/s00382-016-3107-6).
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Modeling Analysis and Prediction Program (MAP)