The performance of 28 CMIP6 models in simulating the Southeast Asian (SEA) climate is investigated. An evaluation methodology is developed to evaluate spatiotemporal patterns of precipitation, near‐surface temperature, and 850‐hPa wind. Mean annual cycles of temperature and rainfall are assessed separately over Indochina, the Maritime Continent, and the Philippines; and the summer and winter seasons are selected for studying spatial patterns. Within these distinctions, statistics comparing the models to reference data are calculated. The patterns' shape and phase are notably studied, and wind direction differences are assessed specifically over the most major wind flows. We present a scoring procedure allowing us to give each model a unique score reporting on the diverse evaluation aspects, hence establishing a ranking. The process rests on a scoring function growing exponentially with the performance: it favours the models combining good performances according to the largest number of criteria. The assessment highlights EC‐Earth3 and EC‐Earth3‐Veg, which conduct excellent simulations of the regional patterns of rainfall and wind. Their temperature outputs are also reliable, but CNRM‐CM6 ranks first for this variable, while finishing third globally. Local differences are discussed: we emphasize, among other things, the diverse impact of topography on temperature and rainfall, or the frequent deviation of winter winds circulating from the South China Sea to the Java Sea. In addition, a similarity study reveals major difficulties for simulating near‐equatorial annual cycles of temperature and precipitation whereas the summer monsoon spatial rainfall patterns bring out the largest discrepancies. In any event, the top models pointed out by our ranking constitute a high‐performance subset that further climate modelling experiments in SEA can rely on.

This study comprehensively assesses the performance of 29 Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs) and their ensemble mean (ENS_MEAN) over Vietnam. The spatiotemporal variability of near-surface temperature and precipitation is thoroughly evaluated for the 30-year historical period of 1985–2014. Results show that the models can reasonably reproduce the observational annual cycles and spatial distribution of temperature and precipitation, though their performances vary across the seven climatic sub-regions of Vietnam. Due to their coarse resolutions, the models produce warm biases over certain highland and mountainous areas, and many of them cannot reproduce the rainy season shift from summer in most sub-regions toward the end of the year in Central Vietnam. Finally, these results are summarized, and a performance score is assigned to each model, inferring a ranking. The top three models are EC-Earth3-Veg, EC-Earth3, and HadGEM3-GC31-MM. Although created by simply averaging all the models, ENS_MEAN can compete with the best GCMs and ranks 4th overall. In the same model family, the higher-resolution experiment exhibits a higher ranking than the lower-resolution one. The results of this study can provide a reference for the choice of appropriate CMIP6 GCMs in the upcoming downscaling activities in Vietnam.