ArticleScience advances2026
Extreme-range precipitation probability across global weather systems.
Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
Precipitating weather systems are major contributors to hazardous extreme rain, yet weather and climate models struggle to capture their dynamics and relative impacts. Using high-resolution observations, we examine precipitation probability distributions at hourly timescale linked to major system types across the globe. We show that the high-intensity tails of these distributions share a typical shape, which can be characterized by an intensity scale. Dynamic processes largely govern this universal shape, while thermodynamic factors modulate its magnitude. We find that intensity scales of major contributing systems largely match those of total precipitation due to shared thermodynamic environments, dominance of intense systems, and modest variations in dynamic scales. This universality of various system types' precipitation probability tail supports risk assessment without overly depending on weather-type identification for most regions. We identify exceptions where intense tropical low-pressure systems or mesoscale convective system co-occurrences disproportionately affect extremes, yielding gray-swan-prone distributions.
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Registered trials
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