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Assessment of potential risks induced by increasing extreme precipitation under climate change

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Abstract

A warmer climate has caused more extreme climate events like the heatwave or extreme precipitation, which has led to a large number of lives and economic losses. In this study, we adopt historical daily precipitation from rainfall estimates on a gridded network (REGEN) and future daily projections from 10 general circulation models (GCMs) to analyze the potential risks of extreme precipitation due to changes in the magnitude and frequency. We calculate the 10-year and 100-year return levels by fitting the partial duration series (PDS) data with the generalized Pareto (GP) distribution. The potential risks are quantified in two terms: by the ratio of the magnitude to the threshold and by the exceedance frequency comparing to the theoretical value. The results show that in the future, about 46% of the world may suffer from mid or high risk of change in extreme precipitation. Most regions show higher risk due to the increased frequency of extreme precipitation events under the RCP8.5 scenario. The high risk of humid regions mainly appears under the RCP8.5 scenario and is mainly driven by frequency change, while that of arid regions appears under both the scenarios and is driven by both the frequency and magnitude change. The tropical rainforest climate areas of South America (SA (N)), the tropical savanna or tropical wet monsoon and tropical dry areas of South Asia (SA), and the subarctic climate areas of Northern Asia (NOA) may suffer more risks from the view of both magnitude and frequency changes of extreme precipitation.

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Acknowledgments

This work was supported by the National Key Research and Development Program of China (Grant Number: 2017YFA0605303), the National Natural Science Foundation of China (41877454, 51809251), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA23100401), the Youth Innovation Promotion Association of CAS (No.2019053), and the Young Talents in IGSNRR, CAS (2017RC201).

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Authors and Affiliations

  1. Key Laboratory of Land Surface Patterns and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China

    Hefei Huang, Huijuan Cui & Quansheng Ge

  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    Hefei Huang & Quansheng Ge

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  1. Hefei Huang
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  2. Huijuan Cui
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All authors contributed to the study conception and design. All authors read and approved the final manuscript.

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Correspondence to Huijuan Cui.

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Huang, H., Cui, H. & Ge, Q. Assessment of potential risks induced by increasing extreme precipitation under climate change. Nat Hazards 108, 2059–2079 (2021). https://doi.org/10.1007/s11069-021-04768-9

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