Increasing risk of mass human heat mortality if historical weather patterns recur

Abstract The potential death toll of exceptional extreme heat events is crucial for climate risk analysis and adaptation planning but may not be captured by existing projections. Here we combine machine learning-based projections of five historical European heat waves under present or future global temperatures with empirical exposure–response functions to quantify the potential for extreme heat events to generate mass mortality. For example, if August 2003 meteorological conditions recur at the recent annual global temperature anomaly of 1.5 °C, we project 17,800 excess deaths across Europe in one week, rising to 32,000 at 3 °C. This mortality is comparable to peak COVID-19 mortality in Europe and is not substantially reduced by climate adaptation currently observed across Europe. Our results suggest that while mitigating further global warming can reduce heat mortality, mass mortality events remain plausible at near-future temperatures despite current adaptations to heat.