Abstract

Using 32 CMIP5 (Coupled Model Intercomparison Project Phase 5) models, this study examines the veracity in the simulation of cloud amount and their radiative effects (CREs) in the historical run driven by observed external radiative forcing for 1850–2005, and their future changes in the RCP (Representative Concentration Pathway) 4.5 scenario runs for 2006–2100. Validation metrics for the historical run are designed to examine the accuracy in the representation of spatial patterns for climatological mean, and annual and interannual variations of clouds and CREs. The models show large spread in the simulation of cloud amounts, specifically in the low cloud amount. The observed relationship between cloud amount and the controlling large-scale environment are also reproduced diversely by various models. Based on the validation metrics, four models—ACCESS1.0, ACCESS1.3, HadGEM2-CC, and HadGEM2-ES—are selected as best models, and the average of the four models performs more skillfully than the multimodel ensemble average. All models project global-mean SST warming at the increase of the greenhouse gases, but the magnitude varies across the simulations between 1 and 2 K, which is largely attributable to the difference in the change of cloud amount and distribution. The models that simulate more SST warming show a greater increase in the net CRE due to reduced low cloud and increased incoming shortwave radiation, particularly over the regions of marine boundary layer in the subtropics. Selected best-performing models project a significant reduction in global-mean cloud amount of about −0.99% K−1 and net radiative warming of 0.46 W m−2 K−1, suggesting a role of positive feedback to global warming.

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