Large‐Scale Mechanisms Associated With the Predictability of Summer Monsoon Rainfall Over Homogeneous Regions of India in the Latest Seasonal Prediction Models of NMME and IITM ‐ MMCFSv2

ABSTRACT In the present study, we assess the seasonal prediction skill of the latest coupled climate models from the North American Multi‐Model Ensemble (NMME) and the Indian Institute of Tropical Meteorology's Monsoon Mission Coupled Forecast System version 2 (IITM‐MMCFSv2) for predicting Indian Summer Monsoon Rainfall (ISMR) over five homogeneous regions of India. The analysis is carried out over Northeast India (NEI), Central Northeast India (CNEI), West Central India (WCI), Northwest India (NWI) and South Peninsular India (SPI). The role of large‐scale ocean‐atmospheric mechanisms influencing ISMR variability across these regions is also analysed. The results reveal substantial spatial heterogeneity in model performance, with individual models exhibiting region‐specific strengths and weaknesses. The models demonstrate higher skill in predicting rainfall over SPI, CNEI, WCI and NWI, but lower skill over NEI. To improve regional seasonal prediction skill and understand the mechanisms controlling rainfall variability, a Best‐Model Ensemble (BME) is constructed and compared with the Multi‐Model Ensemble (MME). The retrospective BME assessment shows better precipitation correlation than the MME and individual models across the homogeneous regions. However, to address potential selection bias arising from using the same period for model selection and evaluation, a leave‐one‐year‐out cross‐validation approach is applied. The cross‐validated BME correlations indicate that BME predictive skill is region‐dependent. The best‐performing models show a stronger association between regional rainfall and large‐scale sea surface temperature (SST) and upper‐tropospheric circulation patterns, including the El Niño‐Southern Oscillation, East Indian Ocean and northwest Pacific SST variability and velocity potential. However, most models inadequately capture local SST variability, such as cooling in the eastern Pacific, and the complex orographic effects that influence NEI rainfall, resulting in relatively lower precipitation prediction skill over this region. Overall, the results demonstrate that the effectiveness of BME‐based seasonal prediction is region‐dependent and highlight the importance of accounting for model‐selection uncertainty when evaluating regional ISMR prediction skill.