Performance evaluations of CMIP6 and CMIP5 models for precipitation simulation over the Hanjiang River Basin, China

Abstract

Abstract Projecting the climate change impacts on hydrology and water resources relies on the climate scenarios simulated by general circulation models (GCMs), which requires a systematic and comprehensive assessment of the GCMs’ simulation performances at a regional scale. This study evaluates the performances of precipitation simulation over the Hanjiang River Basin (HRB) by six climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6), the corresponding six previous models from the CMIP5, and their multi-model ensemble (MME) based on the observational data in the CN05.1. To our knowledge, this is the first preliminary study in the HRB. The Taylor diagram (including standard deviation, root-mean-square difference, and correlation coefficient) and Taylor skill score are used for the evaluation of GCMs’ precipitation simulation performances. The spatial pattern and temporal pattern over the HRB simulated by CMIP6 and CMIP5 models are compared by relative biases. The results of the Taylor diagram and skill score show that CMIP6 models don't necessarily perform better than the corresponding previous CMIP5 models in simulating precipitation over the HRB. The MME exhibits superior performance compared to that of any individual model, and the CMIP6-MME is more skillful than the CMIP5-MME. As to the spatial and temporal variation characteristics, the precipitation biases are both present in CMIP6 and CMIP5 models, and the bias of the CMIP6-MME is lower than that of the CMIP5-MME. The CMIP6 and CMIP5 models overestimate the precipitation from January to June, and simulate larger precipitation biases in the areas and seasons with less precipitation, while they are lower with more precipitation over the HRB. The findings obtained in this study could provide a scientific reference for the research of future hydrological cycle predictions over the HRB.