Our confidence in future climate projection depends on the ability of climate models to simulate the current climate, and model performance in simulating atmospheric circulation affects its ability of simulating extreme events. In this study, the self-organizing map (SOM) method is used to evaluate the frequency, persistence, and transition characteristics of models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) for different ensembles of daily 500 hPa geopotential height (Z500) in Asia, and then all ensembles are ranked according to a comprehensive ranking metric (MR). Our results show that the SOM method is a powerful tool for assessing the daily-scale circulation simulation skills in Asia, and the results will not be significantly affected by different map sizes. Positive associations between each two of the performance in frequency, persistence and transition were found, indicating that a good ensemble of simulation for one metric is good for the others. The r10i1p1f1 ensemble of CanESM5 best simulates Z500 in Asia comprehensively, and it is also the best of simulating frequency characteristics. The MR simulation of the highest 10 ensembles for the Western North Pacific Subtropical High (WNPSH) and the South Asia High (SAH) are far better than those of the lowest 10. Such differences may lead to errors in the simulation of extreme events. This study will help future studies in the choice of ensembles with better circulation simulation skills to improve the credibility of their conclusions.
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