Investigating the ability of CMIP6 HighResMIP models to simulate rainy season precipitation over the Lancang-Mekong River Basin

The Coupled Model Intercomparison Project Phase 6 (CMIP6) has introduced the High-Resolution Model Intercomparison Project (HighResMIP) experiment, allowing unprecedented simulations and predictions of global climate models with high resolution (more than 50 km). This study evaluates the capability of six Global Climate Models (GCMs) of HighResMIP in reproducing rainy season precipitation in the Lancang-Mekong River Basin. (1) We selected mean precipitation, hourly precipitation frequency and hourly precipitation intensity during the multi-year rainy season as Precipitation Characteristic Indices to evaluate the ability of GCMs. We found that two GCMs, BCC-CSM2-HR and HadGEM3-GC31-HM, demonstrate a strong ability to reproduce the spatial distribution of precipitation indices during the rainy season, outperforming other GCMs and MME-M; (2) Most GCMs and multi-model ensemble mean (MME-M) can reproduce the latitudinal distribution of mean precipitation, hourly precipitation frequency and hourly precipitation intensity, except HadGEM3-GC31-HM (mean precipitation), HiRAM-SIT-LR and NICAM16-8S (hourly precipitation frequency and hourly precipitation intensity); (3) We found that most GCMs overestimate the frequency of light precipitation, which can reach 60%-80%, while the frequency in the ERA5 (the latest fifth generation reanalysis data product launched by the European Centre for Medium-Range Weather Forecasts) is 53.9%. However, almost all GCMs underestimate the frequency of moderate precipitation and heavy precipitation. For torrential precipitation, severe torrential precipitation, and extremely torrential precipitation events, most GCMs overestimate their frequency; and (4) Most GCMs can not simulate hourly precipitation well according to the Taylor diagram, because the correlation coefficients of four GCMs are about 0.1 and their normalized standard deviations are greater than 1. However, EC-Earth3P-HR and MRI-AGCM3-2-S demonstrate relatively better performance, with correlation coefficients of 0.42 and 0.36, and the normalized standard deviations are close to the reference. These findings will improve the understanding of GCM precipitation simulation with high spatial resolution and higher temporal resolution.