Spatial and temporal patterns of precipitation concentration and their associated risks

Global climate change has profoundly altered precipitation distribution patterns, with the "Wet getting Wetter, Dry getting Drier" (WWDD) pattern widely recognized. However, most previous studies have addressed either the temporal or spatial dimensions of precipitation concentration in isolation, leaving a critical gap in understanding their finer-scale changes and their combined effects and interactive risks. Here, we use the Gini coefficient and ERA5-Land daily data (1951-2020) to assess global precipitation concentration in both time and space. Based on long-term trends, we classify regions into WWDD or WDDW patterns. Our results reveal that 46.4% of global land area shows increasing spatial concentration (WWDD), while 67.4% shows increasing temporal concentration (WWDD). Notably, 33.6% of the global land area exhibits a WWDD pattern in both spatial and temporal dimensions. These jointly concentrated regions are especially vulnerable, as precipitation is becoming more uneven in both time and space, increasing the risk of floods, droughts, and other extreme hydrometeorological events. In contrast, regions with increasing concentration in only one dimension may face more specific hazards-such as short-duration intense precipitation or localized runoff surges. These findings have important implications for assessing global precipitation concentration and informing hydrological disaster management strategies.

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Publication Details

Journal
Scientific Reports
Published
2025-09-26
DOI
https://doi.org/10.1038/s41598-025-18721-4
Citations
2
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
2.21
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article

Spatial and temporal patterns of precipitation concentration and their associated risks

Longsheng Li, Yuqin Lai, Xinyi Wang, Jingyi Li et al.
2 citations
Scientific Reports
Climate variability and models
2.21
article

Spatial and temporal patterns of precipitation concentration and their associated risks

Longsheng Li, Yuqin Lai, Xinyi Wang, Jingyi Li, Guolong Chen, Bo Fu, Mengmeng Lu, Bengang Li, Yongye Jiang, Xinhao Suo
article en
2 citations

Abstract

Global climate change has profoundly altered precipitation distribution patterns, with the "Wet getting Wetter, Dry getting Drier" (WWDD) pattern widely recognized. However, most previous studies have addressed either the temporal or spatial dimensions of precipitation concentration in isolation, leaving a critical gap in understanding their finer-scale changes and their combined effects and interactive risks. Here, we use the Gini coefficient and ERA5-Land daily data (1951-2020) to assess global precipitation concentration in both time and space. Based on long-term trends, we classify regions into WWDD or WDDW patterns. Our results reveal that 46.4% of global land area shows increasing spatial concentration (WWDD), while 67.4% shows increasing temporal concentration (WWDD). Notably, 33.6% of the global land area exhibits a WWDD pattern in both spatial and temporal dimensions. These jointly concentrated regions are especially vulnerable, as precipitation is becoming more uneven in both time and space, increasing the risk of floods, droughts, and other extreme hydrometeorological events. In contrast, regions with increasing concentration in only one dimension may face more specific hazards-such as short-duration intense precipitation or localized runoff surges. These findings have important implications for assessing global precipitation concentration and informing hydrological disaster management strategies.

Scientific ReportsVol. 15(1)
Peking University (CN), Chinese Institute for Brain Research (CN)
Openalex Percentile: Top 11%
Climate variability and models
2.21
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