Identifying the Restructuring of Forced Responses and Internal Variability in Soil Moisture–Precipitation Coupling Mechanisms

The spatiotemporal coupling between soil moisture and precipitation is a fundamental pillar of the global hydrological cycle. With the escalating risk of severe droughts and pluvial extremes, a critical question arises: whether observed variations in soil moisture and precipitation coupling are the result of anthropogenic Forced Response (FR) or Internal Variability (IV). While recent benchmarks, such as the Forced Component Estimation Statistical Method Intercomparison Project, have advanced the estimation of forced components from observational data, a significant gap remains: how to leverage these diagnostic tools to elucidate the non-stationary and non-linear interactions across the full moisture spectrum.

This study introduces a statistical attribution framework that reconciles stationary and non-stationary coupling regimes, allowing for a more robust characterization of shifting climate dynamics. We extend the analysis of direct impacts—where FR and IV drivers linearly alter coupled variables—to the assessment of indirect impacts, where drivers exert non-linear influence on mediating variables, which modulate the dynamic sensitivity and strength of the coupling mechanisms. By decoupling these pathways, we move beyond the simple attribution of trends in moisture states; instead, we identify how anthropogenic forcing and internal variability are fundamentally restructuring the feedback mechanisms of the hydrological cycle.