Analyzing and forecasting the Indian Summer Monsoon Rainfall (ISMR) is vital for South Asia’s socio-economic stability. Using 35 climate models from the latest generation of the Coupled Model Intercomparison Project (CMIP6) to simulate and project ISMR, we integrated statistical methods, such as Taylor diagrams, comprehensive rating indicators, and interannual variability scores, to compare performance differences between various models and analyze influencing mechanisms. The results show that the majority of models effectively simulate the climatology of the ISMR. However, they exhibit limitations in accurately capturing its interannual variability. Importantly, we observed no significant correlation between a model’s ability to simulate ISMR’s general climatology and its accuracy in representing annual variability. After a comprehensive assessment, models, like BCC-ESM1, EC-Earth3-Veg, GFDL-CM4, INM-CM5-0, and SAM0-UNICON were identified as part of the prime model mean ensemble (pMME), demonstrating superior performance in spatiotemporal simulations. The pMME can accurately simulate the sea surface temperature changes in the North Indian Ocean and the atmospheric circulation characteristics of South Asia. This accuracy is pivotal for CMIP6’s prime models to precisely simulate ISMR climatic variations. CMIP6 projections suggest that, by the end of the 21st century, ISMR will increase under low, medium, and high emission scenarios, with a significant rise in rainfall under the high emission scenario, especially in the western and northern parts of India. Among the pMME, the projected increase in rainfall across India is more moderate, with an estimated increase of 30%. The findings of this study suggest that selecting the best models for regional climate downscaling research will project regional climate changes more accurately. This provides valuable recommendations for model improvements in the Indian region.

The South Asian summer monsoon (SASM) system, coupled with its intricate topography, presents formidable challenges to the accuracy of global climate models in realistically replicating the regional precipitation distribution. Employing atmospheric-only simulations from the High-Resolution Model Intercomparison Project (HighResMIP), this study rigorously assesses the capability of models with varying horizontal resolutions in simulating SASM precipitation, utilizing metrics such as horizontal configuration, intensity distribution, interannual variability, and long-term trends. The findings suggest that, despite intermodel discrepancies, high-resolution (HR) models exhibit substantial advantages over low-resolution (LR) models in simulating precipitation over complex orography, particularly in key regions such as the Himalayan foothills, the windward slopes of the Western Ghats, and the central–northern Indian plains. Nonetheless, limitations persist in accurately capturing the long-term trends of precipitation. A comprehensive appraisal reveals that the HR models CMCC-CM2-VHR4, EC-Earth3P-HR, ECMWF-IFS-HR, and HadGEM3-GC31-HM demonstrate superior aptitude in simulating the spatiotemporal distribution of precipitation. Analysis of the moisture budget equation reveals that atmospheric moisture variability in South Asia’s principal monsoon regions is primarily governed by the dynamical term dDY, which elucidates the origin of discrepancies in precipitation simulations between HR and LR models. Specifically, the HR model more precisely characterizes atmospheric circulation features and local dynamical processes and more realistically reproduces the activity characteristics of tropical cyclones over the Bay of Bengal. These improvements yield a more realistic dynamical environment for the SASM, thereby enhancing the accuracy and reliability of simulated precipitation distributions. Significance Statement: Our findings reveal that high-resolution (HR) models significantly enhance monsoonal precipitation simulation over the complex terrain of South Asia, effectively reducing wet biases over the Tibetan Plateau and Pakistan regions. We find that CMCC-CM2-VHR4, EC-Earth3P-HR, ECMWF-IFS-HR, and HadGEM3-GC31-HM exhibit superior ability in resolving spatial patterns and interannual variability, resulting from their capacity to better capture atmospheric circulation, orographically driven vertical motions, and synoptic systems like tropical cyclones. These findings underscore the importance of increased model resolution for more reliable representations of monsoon dynamics and precipitation and highlight the need to prioritize HR models in future research.

Multiple monsoon systems impact autumn precipitation in West China; however, their synergistic influence is unknown. Here, we employed statistical analysis of Global Precipitation Climatology Project Version 3.2 precipitation data, European Center for Medium-Range Weather Forecasts ERA5 reanalysis data, and Coupled Model Intercomparison Project model data, and calculated four monsoon indices to analyze the features of the East Asian Monsoon, South Asian Monsoon, Asia Zonal Circulation, and Tibetan Plateau Monsoon, as well as their synergistic impacts on autumn precipitation in West China. The East Asian Monsoon negatively influences autumn precipitation in West China through closed high pressure over Northeast China. The South Asian Monsoon encloses West China between two areas of closed high pressure; strong high pressure to the north guides the abnormal transport of cold air in Northwest China, whereas strong western Pacific subtropical high pressure guides the transport of warm and wet air to West China, which is conducive to the formation of autumn precipitation in West China. During years of strong Asia Zonal Circulation, West China is controlled by an anomalous sinking airflow, which is not conducive to the occurrence of autumn rain. During strong Tibetan Plateau Monsoon, western and southwestern China are affected by plateau subsidence flow, resulting in less precipitation. Based on the CMIP6 model data, the study found that under the SSP5-8.5 emission scenario, the future trends of the four monsoon systems will show significant differences, and the amplitude of autumn and interannual precipitation oscillations in west China will increase.

Madden–Julian Oscillation (MJO) modulates the generation of typhoons (TYs) in the western North Pacific (WNP). Using IBTrACS v04 tropical cyclone best path data, ERA5 reanalysis data, and the MJO index from the Climate Prediction Center (CPC), this paper defines an index to describe the persistent anomalies of the MJO and to examine the statistical characteristics of TYs over 44 years (1978–2021), focusing on the analysis of major differences in environmental conditions after the removal of the ENSO signal over the WNP. The results indicate that the persistent anomalous state of the MJO influences the change in large-scale environmental factors, which, in turn, affects the generation of TYs, as follows: (1) For the I high-value years, the center of the MJO stagnates in the Indian Ocean–South China Sea (SCS), the monsoon trough retreats westward, the warm pool becomes warmer, and the Walker circulation is enhanced. There is stronger upper-level divergence and low-level convergence, larger low-level relative vorticity, higher mid-level relative humidity, and smaller vertical wind shear in the SCS and the seas near the Philippines. Consequently, these conditions foster a conducive environment for TY genesis in the SCS and the seas near the Philippines. (2) For the I low-value years, the center of the MJO stagnates in the WNP–North America region, the monsoon trough extends eastward, the warm pool becomes colder, and the Walker circulation is weakened. Consequently, these conditions are more likely to facilitate TY genesis in the central–eastern WNP. The results show that persistent anomalies in MJO active centers can effectively improve the predictive ability of TY frequency.