Interannual variability of moisture sources and isotopic composition of Meiyu-Baiu rainfall in southwestern Japan: Importance of Asian monsoon moisture for extreme rainfall events

The interannual variability of Meiyu-Baiu rainfall has amplified in recent decades. Observational and modeling efforts have revealed large-scale circulations could affect variability of Meiyu-Baiu rainfall by altering moisture sources and transport mechanisms. However, the contributions and thermodynamic processes of major moisture sources, along with their interannual variability, remain unclear. To better understand the underlying atmospheric processes responsible for interannual variability of Meiy-Baiu rainfall, we utilized an isotopic regional spectral model to investigate the moisture sources and isotopic composition of Meiyu-Baiu rainfall in southwestern Japan from 2004 to 2023. Asian Monsoon (AM) moisture in middle levels contributed more (51.4%) rainfall with lower δ 2 H and higher d-excess in heavy Meiyu-Baiu seasons. Extreme rainfall events showed lower δ 2 H and higher d-excess with more contribution (57.8%) from AM moisture at middle levels with high precipitation efficiency. Enhanced warm AM moisture feeds the condensation process and enhances atmospheric instability in the middle levels. This facilitates deep convection, leading to more extreme rainfall during heavy seasons. Compared with Eulerian moisture tagging method, Lagrangian backward trajectory method underestimated contribution of AM moisture, due to higher precipitation efficiency at higher altitudes, resulting from stronger convection and ascent accompanied with more precipitation and rainout in the upstream AM regions. The study highlights importance of AM moisture for extreme Meiyu-Baiu rainfall in East Asia. The findings providing valuable insights into understanding the interannual variability of water cycle in East Asia, as well as to improving seasonal forecasts and near-future predictions of Meiyu-Baiu rainfall. • AM moisture at middle levels had lower δ and higher d-excess in heavy season. • Extreme events, characterized by enhanced AM moisture, increased in heavy season. • Enhanced AM moisture with high precipitation efficiency facilitates extreme rainfall. • Lagrangian method underestimated AM moisture contribution than Eulerian method. • Underestimation of AM moisture due to high precipitation efficiency and more rainout.