Replicability of Annual and Seasonal Precipitation by CMIP5 and CMIP6 GCMs over East Asia

Abstract

global climate models (GCMs) structure is a source of uncertainty in climate change projections. Therefore, evaluation of the performances of GCMs is crucial for development of adaptation and mitigation measures and risk reduction against climate change impacts. This study quantified the performances of 10 GCMs of the Coupled Model Intercomparison Project 5 (CMIP5) and their CMIP6 equivalents in replicating precipitation over East Asia during 1975–2005. The CMIP5 and CMIP6 GCMs and their multi-model ensembles (MMEs) were annually and seasonally compared with the Global Precipitation Climatology Centre (GPCC) precipitation. Compromise Programming was used to rank GCMs by aggregating their scores obtained using statistical performance indices. Taylor diagram was used to assess their relative performances and GCMs' ability to replicate seasonal precipitation distribution was evaluated. Results revealed most CMIP6 GCMs' have better replicability of GPCC precipitation than CMIP5 GCMs. The MME mean of the CMIP6 showed better replicability of annual and seasonal GPCC precipitation than that of CMIP5. The CMIP6 MME also showed efficiency in simulating the seasonal precipitation distribution over East Asia. This study indicates improvements of some CMIP5 GCMs in their CMIP6 equivalents over East Asia. Findings from this study can be significant to policy makers and engineers in reducing the uncertainties in prediction of events such as floods and droughts.