Performance evaluation of surface air temperature simulated by the Beijing Climate Central Climate Model based on the climate complexity

In order to evaluate the simulation effect of the model on the dynamic characteristics of the climate system, the approximate entropy method was used to analyze the complexity of surface air temperature (SAT) based on observational data (CN05.1) and the model-simulated data by the Beijing Climate Central Climate Model (BCC-CSM2-MR) in this study. We investigated whether the simulated climate model data exhibited complexity characteristics similar to real-world meteorological elements. In this scenario, we could assess the climate model’s performance by comparing the complexity of observed and simulated data. The results indicate that the BCC-CSM2-MR model can accurately reflect the complexity of SAT in China. When considering the entire year, the model exhibited greater complexity in the simulated SAT than the observations in most regions of China, indicating an overestimation of complexity by the model. When examining different seasons, the model’s complexity was similar to the observations in spring, summer, and winter, indicating a better performance during these seasons. In contrast, the simulated performance is poor during autumn, mainly due to an overestimation of complexity in Qinghai, south-central Xinjiang, and western Xizang.