Atmospheric rivers (ARs) are essential components of the global hydrological cycle, with profound implications for water resources, extreme weather events, and climate dynamics. Yet, the statistical organization and underlying physical mechanisms of AR intensity and evolution remain poorly understood. Here we apply methods from statistical physics to analyze the full life cycle of ARs and identify universal signatures of self-organized criticality. We demonstrate that AR morphology exhibits nontrivial fractal geometry, while AR event sizes—quantified via integrated water vapor transport—follow robust power-law distributions, displaying finite-size scaling. To interpret these emergent behaviors, we develop a moisture avalanche model that reproduces the observed scaling laws and links them to threshold-driven moisture transport and precipitation dissipation. These scaling properties persist under warming scenarios, suggesting that ARs operate near a critical state as emergent, self-regulating systems. Concurrently, we observe a systematic poleward migration and intensification of ARs, driven by thermodynamic amplification and dynamical reorganization. Our findings establish a statistical physics framework for ARs, connecting critical phenomena to the spatiotemporal structure of extreme events in a warming climate.

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• Classical statistical mechanics
• Climate research