Strengthening Coupling Between Vegetation and Soil-Atmosphere Compound Drought Over the Past Two Decades

Soil-atmosphere compound drought (SACD) significantly impacts vegetation, with effects expected to intensify under global warming. However, the dynamic coupling relationship between vegetation and SACD considering the optimal time lag remains unclear. To address this, we first employed copulas to develop a SACD index at temporal scales ranging from 1 to 24 months. Based on this index, the coupling relationship represented by the maximum correlation coefficient (R_max) and the optimal time lag (T_opt) between the Leaf Area Index and the SACD was examined. Furthermore, the coupling degree between the two was explored both temporally and spatially. The results revealed a significant nonlinear trend in both R_max and T_opt, with turning points identified using the Ensemble Empirical Mode Decomposition occurring between 2010–2014 and 2011–2015, respectively. Additionally, it was found that the temporal coupling degree was strong, while the spatial coupling was initially weaker but showed an increasing trend, particularly in water-limited regions. Land surface model simulations indicated that CO₂ was the dominant driver of the vegetation-drought coupling relationship and degree. Machine learning and SHapley Additive Explanations underscored the critical importance of meteorological variables, with radiation, precipitation and temperature being identified as the most influential meteorological factors. Finally, based on the Peter-Clark Momentary Conditional Independence Plus, the complex causal relationship network between meteorological factors and the vegetation-drought coupling was revealed. Our study highlights the importance of examining the dynamic coupling between vegetation and SACD, with the findings providing valuable insights to support ecosystem sustainability under climate change.