Rainfall seasonality changes and underlying climatic causes in global land monsoon regions

Changes in rainfall seasonality can have far-reaching impacts on the livelihood of population, agricultural production, and ecosystem sustainability. However, the changes in rainfall seasonality and associated climatic causes are largely unclear, especially in global land monsoon regions. Here, we analyzed the variations of rainfall seasonality during 1960–2022, and explored the possible effects of global climate teleconnections (CTs) on rainfall seasonality changes in global land monsoon regions using interpretable machine learning and multivariate wavelet coherency method. The results show that rainfall seasonality weakens significantly in northeastern South Asian, northeastern South American, and most parts of southern North African and South African monsoon regions, but enhances significantly in southern South Asian, northern North African, and southwestern South American monsoon regions. Rainfall seasonality also experiences an abrupt change in all hotspots during 1960–2022. We also find that many CTs are nonmonotonically related to rainfall seasonality in these hotspots, and the key CTs that explain the variations in rainfall seasonality differ across different hotspots using interpretable machine learning. The coupled influences of the key CTs on rainfall seasonality are also significant at certain scales during different periods in these hotspots. However, the key CTs have undergone changes, with stronger impacts on rainfall seasonality in almost all hotspots since 1990s. The findings of this study offer a robust scientific foundation that significantly contributes to enhancing agricultural productivity, fostering ecosystem sustainability, and promoting water resources management.