Abstract
AbstractThe simultaneous occurrence of extremely wet winters at multiple locations in the same region can contribute to widespread flooding and associated socio‐economic losses. However, the spatial extent of precipitation extremes (i.e., the area in which nearby locations experience precipitation extremes simultaneously) and its future changes are largely overlooked in climate assessments. Employing new multi‐thousand‐year climate model simulations, we show that under both 2.0 °C and 1.5 °C warming scenarios, wintertime total precipitation extreme extents would increase over about 80%–90% of the Northern Hemisphere extratropics (i.e., of the latitude band 28°–78°N). Stabilizing at 1.5 °C rather than 2.0 °C would reduce the average magnitude of the increase by 1.7–2 times. According to the climate model, the increased extents are caused by increases in precipitation intensity rather than changes in the spatial organization of the events. Relatively small percentage increases in precipitation intensities (e.g., by 4%) can drive disproportionately larger, by 1–2 orders of magnitude, growth in the spatial extents (by 93%).
Highlights
Wet winters resulting from one or multiple precipitation events can contribute to flooding leading to severe societal, natural, and economic impacts
Given that simultaneous extremely wet winters occurring at multiple locations within the same region can enhance regional impacts, we analyze the extreme extents of these events employing the precipitation spatial scale
The hemispheric median of the spatial scale extremes is about 28 × 105 km2, indicating that the considered events potentially extend across multiple countries
Summary
Wet winters resulting from one or multiple precipitation events can contribute to flooding leading to severe societal, natural, and economic impacts. In a future warmer climate, a moister atmosphere will favor higher precipitation magnitudes, while changes in the atmospheric circulation, for example, storm track variations, may modulate both precipitation magnitudes and spatial patterns (e.g., Bevacqua, Zappa, et al, 2020; O'Gorman & Schneider, 2009). As a result, these mechanisms may change the spatial extent of seasonal precipitation extremes. A large sample size of data is required to analyze extremes of this type of spatially compounding event, we employ new multi-thousand-year climate model simulations
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