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 (ΔTave and ΔTmax) and precipitation (ΔPave and ΔPmax) changes during maize growing seasons. We find that ΔTave, ΔTmax, and ΔPmax 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 ΔTave and ΔTmax. 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.

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