Global Drought Complexity in a Warming Climate: A concentric framework

Drought, a complex natural hazard shaped by intertwined climatic and terrestrial feedbacks, is difficult to predict. Here, we examine global hydroclimatic hotspots to uncover how drought evolves through nonlinear, state-dependent mechanisms. Our review and analysis show that moderate moisture deficits often intensify abruptly due to amplifying feedbacks, whereas severe deficits become self-limiting as the coupling between land and atmosphere weakens. Diagnostic tools such as wavelet coherence, mutual information, and coupling indices show that drought predictability varies across regions, including the Southwestern United States, Australia, and South Asia, reflecting differences in ENSO–PDO teleconnections, soil moisture memory, and ecosystem inertia. We compile these findings into a concentric framework that links climatic drivers, land–surface, and feedback memory. This framework explains the inherent limits of linear persistence models and highlights the need to incorporate nonlinear land–atmosphere interactions in next-generation drought prediction and adaptive water management under a warming climate.