Evaluating the Seasonal Cycle of the South China Sea Monsoon in CMIP6 Models

In the present study, the performance of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the seasonal cycle of the South China Sea (SCS) monsoon is evaluated by comparing the model outputs with observations,  the NCEP–NCAR reanalysis, and the NOAA OLR-Climate Data Record (CDR). The results indicate that there exist differences in the performance of models for various SCS monsoon indices. The models with the best performance for simulating the zonal circulation index (ZCI) and meridional circulation index (MCI) are TaiESM1 and CMCC-CM2-SR5 respectively, while ACCESS-CM2 and GISS-E2-1-G exhibit better performance for simulating the convection index (CI) than other CMIP6 models selected in this study. Additionally, the multi-model ensemble mean (MME) can replicate the seasonal cycles of the SCS monsoon well, yet both convection and circulation present a considerable bias in May, during the SCS summer monsoon onset period. The biases associated with the three physical processes, namely the sea–land thermal contrast, the northward-propagating intraseasonal oscillation (ISO), and the convection of Bay of Bengal, contribute significantly to the large bias of ZCI. However, only the biases related to the convection of Bay of Bengal and the sea–land thermal contrast have a significant impact on the large biases of MCI in May. The large biases of CI are mainly attributed to the bias of the convection of Bay of Bengal, while the northward-propagating ISO plays a supplementary role.