摘要：Marked by large interannual variability, East Asian summer monsoon (EASM) rainfall has profound socio‐economic impacts through its dominant influence on floods and droughts. Improving predictions of the interannual variations of EASM rainfall has important implications for over 20% of the world's population. While coupled modeling systems have demonstrated some prediction skill related to the El Niño Southern Oscillation with remote influence on EASM rainfall, the impact of soil moisture has heretofore not been systematically investigated. Using a weakly coupled data assimilation (WCDA) system to constrain the soil moisture and soil temperature in a coupled climate model with a global land data assimilation product, this study demonstrates significant improvements in simulating the interannual variations of EASM rainfall, capturing the notable shift to a “wetter‐South‐drier‐North” rainfall pattern in China in the early 1990s. Hindcast simulations initialized with the well‐balanced states from a coupled simulation with WCDA also show significant multi‐year rainfall prediction skill over East China and Tibetan Plateau. Improvements in predicting the EASM rainfall are attributed to the strong land‐atmosphere coupling in large areas over China, which allows improved predictions of soil moisture to influence precipitation through soil moisture‐precipitation feedback, and the effects of land anomalies on the EASM circulation. This study highlights the significant contribution of land to the interannual predictability of EASM rainfall, with a great potential to advance skillful interannual predictions of benefit to the large populations influenced by the annual whiplash of the summer monsoon rain. Plain language Abstract The East Asian summer monsoon (EASM) rainfall provides water for over 20% of the world's population but large variability of the monsoon rain can wreak havoc through flood and drought. Previous efforts focusing largely on the El Niño Southern Oscillation to improve interannual prediction of EASM rainfall have provided limited success. By developing a weakly coupled data assimilation system to constrain the soil moisture and soil temperature with observations in a coupled climate model, we demonstrate significant improvements in simulations and hindcasts of EASM rainfall at interannual timescale, attributable to the local and remote impacts of land‐atmosphere interactions. Our results motivate the need to systematically evaluate the contributions of land versus ocean to interannual climate predictability worldwide.
