Emergent constraints on future change projections of mean and extreme temperature and precipitation in the global maize harvesting area

Bibliographic Data

ID15549023
AuthorsHideo Shiogama (0000-0001-5476-2148, National Institute for Environmental Studies, corresponding author), Masashi Okada (0000-0002-5111-0483, National Institute for Environmental Studies), Yuji Masutomi (0000-0003-0083-6337, National Institute for Environmental Studies), Toshichika Iizumi (0000-0002-0611-4637, National Agriculture and Food Research Organization)
Year2025
Volume21
Issue2
Pages024002-024002
Publication date2025-12-29
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironmental Research Letters (JOURNAL)
Journal identifiersISSN: 1748-9326 • E-ISSN: 1748-9326
PublisherIOP Publishing (PUBLISHER • GB)
DOI10.1088/1748-9326/ae3194
OpenAlexW7117564378
LanguageEN
References cited68

Maize cultivation faces increasing risks from climate change, particularly because of increasing temperatures and extreme weather events. This study investigates whether the ‘hot’ Earth system models (ESMs) of the Coupled Model Intercomparison Project Phase 6, whose past warming trends are typically greater than the observations, tend to overestimate future temperature and precipitation changes across the global maize harvesting areas. By applying an emergent constraint (EC) approach to 30 ESMs, we assess the future mean and extreme temperature (Δ T ave and Δ T max ) and precipitation (Δ P ave and Δ P max ) changes during maize growing seasons. We find that Δ T ave , Δ T max , and Δ P max averaged over the global harvesting regions are significantly correlated with the past global mean temperature trends, indicating that hot ESMs tend to overestimate the future changes in these variables. ECs reduce the inter-ESM variances in these projections by 43%, 39%, and 18%, respectively. Notably, the regions with the highest maize production, such as the USA and China, are projected to experience the greatest increases in Δ T ave and Δ T max . The fraction of the global maize production exposed to historically rare high temperatures increases substantially in the raw projections but is moderated when ECs are applied. These findings suggest that the use of hot ESMs may lead to overestimated impacts of climate change on maize and that EC methods offer a robust pathway for refining impact assessments

Climate change · Climate extremes · Coupled model intercomparison project · Global change · Global temperature · Global warming · Mean radiant temperature · Precipitation · Climate Change and Health Impacts · Climate change impacts on agriculture · Climate variability and models

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