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Evaluation of CMIP5 continental precipitation simulations relative to satellite‐based gauge‐adjusted observations

The objective of this study is to cross‐validate 34 Coupled Model Intercomparison Project Phase 5 (CMIP5) historical simulations of precipitation against the Global Precipitation Climatology Project (GPCP) data, quantifying model pattern discrepancies, and biases for both entire distributions and their upper tails. The results of the volumetric hit index (VHI) analysis of the total monthly precipitation amounts show that most CMIP5 simulations are in good agreement with GPCP patterns in many areas but that their replication of observed precipitation over arid regions and certain subcontinental regions (e.g., northern Eurasia, eastern Russia, and central Australia) is problematical. Overall, the VHI of the multimodel ensemble mean and median also are superior to that of the individual CMIP5 models. However, at high quantiles of reference data (75th and 90th percentiles), all climate models display low skill in simulating precipitation, except over North America, the Amazon, and Central Africa. Analyses of total bias (B) in CMIP5 simulations reveal that most models overestimate precipitation over regions of complex topography (e.g., western North and South America and southern Africa and Asia), while underestimating it over arid regions. Also, while most climate model simulations show low biases over Europe, intermodel variations in bias over Australia and Amazonia are considerable. The quantile bias analyses indicate that CMIP5 simulations are even more biased at high quantiles of precipitation. It is found that a simple mean field bias removal improves the overall B and VHI values but does not make a significant improvement at high quantiles of precipitation.