Combined emergent constraints on future extreme precipitation changes

Hideo Shiogama (), Michiya Hayashi, Nagio Hirota, Tomoo Ogura, Hyungjun Kim and Masahiro Watanabe
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Hideo Shiogama: National Institute for Environmental Studies
Michiya Hayashi: National Institute for Environmental Studies
Nagio Hirota: National Institute for Environmental Studies
Tomoo Ogura: National Institute for Environmental Studies
Hyungjun Kim: Korea Advanced Institute of Science and Technology
Masahiro Watanabe: University of Tokyo

Nature Communications, 2025, vol. 16, issue 1, 1-10

Abstract: Abstract Recent studies have shown that the observed global warming trend over recent decades provides efficient constraints not only for future global mean temperature increases (ΔTgm) across Earth system models but also for changes in several climate variables that include significant ΔTgm–related uncertainty. However, ΔTgm–related emergent constraints (ECs) cannot reduce the uncertainty unrelated to ΔTgm. Here, to overcome this limitation, we develop an EC method and apply it to future changes in the annual maximum daily precipitation in order to reduce uncertainty therein. An EC for precipitation sensitivity based on historical extreme precipitation biases is combined with the constrained ΔTgm. This combined EC decreases the variance of the global mean precipitation by 42%, an improvement from only using temperature (resulting in 26% reduction), and the variance of regional precipitation by ≥ 30% in 24% of the globe (whereas ≥ 30% reduction is only seen in 2% of the globe with the temperature-related EC).

Date: 2025
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DOI: 10.1038/s41467-025-60385-1

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