Constrained Precipitation Extremes Reveal Unequal Future Socioeconomic Exposure

Abstract Extreme precipitation can lead to major flooding, impacting human health and safety. Thus, reliable projections of population and GDP exposure to future extreme precipitation are imperative. Here, we quantify future precipitation characteristics from robust emergent constraint relationships between historical and future monthly precipitation extremes (99th percentile) across 19 CMIP6 models ( r 2 > 0.7 in 74–84% of 0.5° global land grids), and narrow uncertainty by 37.0–39.5% (absolute reduction being 0.753–0.774 mm/day). The constrained grid‐averaged future 99th percentile extreme is 6.96 ± 0.0059, 7.03 ± 0.0061, 7.11 ± 0.0063, and 7.29 ± 0.0067 mm/day, under SSP126, SSP245, SSP370, and SSP585, respectively, which exceeds historical extremes substantially in terms of intensity (12.9–19.7%) and frequency (1.6–2.3 times more). Future population and GDP exposed to 99th percentile extreme precipitation grow quickly, and are projected to exceed 1 million people in 27–40 countries and 10 billion USD (2005 Purchasing‐Power Parity) in 48–77 countries. Growth of future population exposure is dominated by an increase in extreme precipitation frequency rather than a rise in population, especially in developed countries. GDP exposure is controlled by the coupled effects of rapid socio‐economic development and significant shifts in precipitation frequency. Using indices of socio‐economic vulnerability, government effectiveness and economic freedom, we identify the unequal situation that high‐risk countries with high exposure are commonly characterized by low GDP per capita and high sociopolitical instability.

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Publication Details

Journal
Earth s Future
Published
2024-12-01
DOI
https://doi.org/10.1029/2024ef004825
Citations
4
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
1.13

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article

Constrained Precipitation Extremes Reveal Unequal Future Socioeconomic Exposure

Zhonghua Yang, Yao Yue, Chiyuan Miao, Louise Slater et al.
4 citations
Earth s Future
Climate variability and models
1.13
article

Constrained Precipitation Extremes Reveal Unequal Future Socioeconomic Exposure

Zhonghua Yang, Yao Yue, Chiyuan Miao, Louise Slater, Ziyi Liu, Yuanfang Chai, Alistair G.L. Borthwick, Xiaofan Luan
article en
4 citations

Abstract

Abstract Extreme precipitation can lead to major flooding, impacting human health and safety. Thus, reliable projections of population and GDP exposure to future extreme precipitation are imperative. Here, we quantify future precipitation characteristics from robust emergent constraint relationships between historical and future monthly precipitation extremes (99th percentile) across 19 CMIP6 models ( r 2 > 0.7 in 74–84% of 0.5° global land grids), and narrow uncertainty by 37.0–39.5% (absolute reduction being 0.753–0.774 mm/day). The constrained grid‐averaged future 99th percentile extreme is 6.96 ± 0.0059, 7.03 ± 0.0061, 7.11 ± 0.0063, and 7.29 ± 0.0067 mm/day, under SSP126, SSP245, SSP370, and SSP585, respectively, which exceeds historical extremes substantially in terms of intensity (12.9–19.7%) and frequency (1.6–2.3 times more). Future population and GDP exposed to 99th percentile extreme precipitation grow quickly, and are projected to exceed 1 million people in 27–40 countries and 10 billion USD (2005 Purchasing‐Power Parity) in 48–77 countries. Growth of future population exposure is dominated by an increase in extreme precipitation frequency rather than a rise in population, especially in developed countries. GDP exposure is controlled by the coupled effects of rapid socio‐economic development and significant shifts in precipitation frequency. Using indices of socio‐economic vulnerability, government effectiveness and economic freedom, we identify the unequal situation that high‐risk countries with high exposure are commonly characterized by low GDP per capita and high sociopolitical instability.

Earth s FutureVol. 12(12)
Sichuan University (CN), Beijing Normal University (CN), Wuhan University (CN), University of Oxford (GB), State Key Laboratory of Hydraulics and Mountain River Engineering, University of Plymouth (GB), University of Edinburgh (GB)
NERC Environmental Bioinformatics Centre, UK Research and Innovation, Sight Research UK, National Natural Science Foundation of China, Sichuan University, State Key Laboratory of Hydraulics and Mountain River Engineering, Natural Environment Research Council
Decent work and economic growth
Openalex Percentile: Top 22%
Climate variability and models
1.13
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