A New Perspective on Drought Propagation: Causality

Abstract The essence of propagation from meteorological to hydrological drought is the cause‐effect relationship between precipitation and runoff. This study challenged the reliability of applying linear or non‐linear correlation (i.e., closeness/similarity, a non‐directional scalar) to study drought propagation (i.e., causality, a directional vector). Meanwhile, in the field of hydrometeorology, causality analysis is burgeoning in model simulations, but still rare in analyzing the observations. Therefore, this study aims to provide a new perspective on drought propagation (i.e., causality) using convergent cross mapping (CCM) based on pure observations. Compared with the results in previous studies, the effectiveness of applying causality analysis in drought propagation study was proven, indicating that causality analysis would be more powerful than correlation analysis, especially for detecting drought propagation direction.

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