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Spatio-Temporal Evolution and Circulation Links of Summer Precipitation in Central Asia: Roles of Pacific and Atlantic Sea-Surface Temperature Modes

Oct 2026 · Remote Sensing · 0 citations · 45 references

Abstract

Central Asia, as a typical arid and semi-arid region, experiences precipitation variability that critically influences water security and ecological balance. Based on ERA5-Land reanalysis data and 14 large-scale climate indices from 1980 to 2025, this study investigates the spatiotemporal evolution of summer precipitation and its physical attribution by employing the Mann–Kendall trend test, Pettitt change-point detection, variance inflation factor (VIF), least absolute shrinkage and selection operator (LASSO), partial correlation analysis, multiple linear regression, and composite analysis. Summer precipitation shows a statistically significant decreasing trend of −0.376 mm/season per year (p = 0.031), with a significant change point in 2006; the regional mean declined by 15.75% after the change point. VIF and LASSO screening identify four candidate variables: the Pacific Decadal Oscillation (PDO), the Oceanic Niño Index (ONI), the Trans-Niño Index (TNI), and the Tropical Southern Atlantic Index (TSA). The multiple linear regression model explains 34.8% of the variance in summer precipitation (R2 = 0.348, p = 0.0013), ranking ONI > PDO > TSA > TNI based on absolute standardized coefficients. PDO is positively correlated with summer precipitation, whereas ONI, TNI, and TSA are negatively correlated. PDO, ONI, and TNI are statistically significant after FDR correction (q < 0.05), while TSA is not significant (q = 0.061). Composite analysis reveals distinct 500 hPa circulation anomalies during positive and negative phases of ONI, PDO, and TNI over Central Asia, providing a circulation-based interpretation of their influence on summer precipitation. This study identifies PDO, ENSO-related Pacific SST modes (ONI and TNI), and TSA as variables linked to summer precipitation in Central Asia, providing scientific support for regional climate monitoring and water resource management.

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