Fingerprint‐Based Attribution and Constrained Projection of Global Risk of Daily Compound Hot Extremes

Abstract Compound hot extremes (CHEs)—the concurrence of daytime and nighttime heat—have been increasing under anthropogenic warming, causing serious damage to human society and ecosystems. However, the anthropogenic fingerprint in past and future changes in daily CHEs and the corresponding population exposure remain unclear. Here, using a fingerprint‐based detection and attribution method, we quantify contributions of different external forcings to the historical increase in CHEs by defining three daily scale metrics: the probability ratio (PR) of CHEs and the proportion of CHEs in the number of extreme hot days/nights (PTday/PTnight). All three metrics increased significantly by 117.9%, 128.7%, and 133.4% globally from 1950 to 2014. It is very likely (>90%) for human to leave fingerprints in increasing daily CHEs. The increases in PR, PTday, and PTnight that are attributable to greenhouse gas emissions are 121.2%, 123.1%, and 121.5%, respectively. By the end of the 21st century under a high‐emission scenario, fingerprint‐constrained projections show the PR of CHEs will be about 60 times higher than the climatological period, with around 41% of hot days and 49% of hot nights as CHEs, reducing the magnitude compared to raw projections. In some regions such as mid and high‐latitudes, almost all daytime or nighttime extreme‐heat events would become CHEs. The growing difference between CHE days per person and per unit of land area suggests that CHEs will disproportionately affect densely populated areas. Our results indicate that adaptive measures are required to alleviate the increasing proportion of CHEs and the disproportionate population exposure in densely populated areas.

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Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2025-06-28
DOI
https://doi.org/10.1029/2024jd041986
Citations
4
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
4.42

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article

Fingerprint‐Based Attribution and Constrained Projection of Global Risk of Daily Compound Hot Extremes

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4 citations
Journal of Geophysical Research Atmospheres
Climate variability and models
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article

Fingerprint‐Based Attribution and Constrained Projection of Global Risk of Daily Compound Hot Extremes

Yansong Guan, Xiongpeng Tang, Xueying Li, Dongdong Kong, Louise Slater, Aminjon Gulakhmadov, Xihui Gu, Lunche Wang, Liangwei Li, Khosro Ashrafi, Xiang Zhang
article en
4 citations

Abstract

Abstract Compound hot extremes (CHEs)—the concurrence of daytime and nighttime heat—have been increasing under anthropogenic warming, causing serious damage to human society and ecosystems. However, the anthropogenic fingerprint in past and future changes in daily CHEs and the corresponding population exposure remain unclear. Here, using a fingerprint‐based detection and attribution method, we quantify contributions of different external forcings to the historical increase in CHEs by defining three daily scale metrics: the probability ratio (PR) of CHEs and the proportion of CHEs in the number of extreme hot days/nights (PTday/PTnight). All three metrics increased significantly by 117.9%, 128.7%, and 133.4% globally from 1950 to 2014. It is very likely (>90%) for human to leave fingerprints in increasing daily CHEs. The increases in PR, PTday, and PTnight that are attributable to greenhouse gas emissions are 121.2%, 123.1%, and 121.5%, respectively. By the end of the 21st century under a high‐emission scenario, fingerprint‐constrained projections show the PR of CHEs will be about 60 times higher than the climatological period, with around 41% of hot days and 49% of hot nights as CHEs, reducing the magnitude compared to raw projections. In some regions such as mid and high‐latitudes, almost all daytime or nighttime extreme‐heat events would become CHEs. The growing difference between CHE days per person and per unit of land area suggests that CHEs will disproportionately affect densely populated areas. Our results indicate that adaptive measures are required to alleviate the increasing proportion of CHEs and the disproportionate population exposure in densely populated areas.

Journal of Geophysical Research AtmospheresVol. 130(13)
Helmholtz Centre for Environmental Research (DE), Academy of Sciences of the Republic of Tajikistan (TJ), Nanjing University of Information Science and Technology (CN), University of Tehran (IR), Beijing Normal University (CN), China University of Geosciences (CN), University of Oxford (GB), Nanjing Hydraulic Research Institute (CN)
National Natural Science Foundation of China, Changjiang River Scientific Research Institute, National Key Research and Development Program of China
Openalex Percentile: Top 6%
Climate variability and models
4.42
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