近日，美国斯坦福大学Christopher W. Callahan团队报道了量化气候变化和适应对前所未有的极端高温事件死亡率的贡献。相关论文发表在2025年12月16日出版的《美国科学院院刊》杂志上。

理解极端高温事件的致死效应，是气候变化风险分析与适应决策的核心。准确评估这些影响需综合考虑持续高温天气对死亡率的叠加效应、人为强迫导致的死亡率变化，以及热适应可能产生的补偿作用。

研究组重新审视了2003年8月法国热浪事件——该地区拥有丰富的气候与死亡率数据，堪称经典案例，以深入解析上述影响因素。结果发现：标准的高温-死亡率暴露-反应函数对2003年8月超额死亡的预测值较实际低55%，而引入高温日的时序累积效应后，模型结果与观测死亡率更为吻合。在考量累积效应并运用机器学习方法进行单一事件气候归因后，研究组确认2003年8月有6079例死亡可归因于气候变化。最后研究表明，法国近年实施的热适应措施已将类似2003年的未来极端高温事件预估死亡人数降低了75%以上。

附：英文原文

Title: Quantifying the contributions of climate change and adaptation to mortality from unprecedented extreme heat events

Author: Callahan, Christopher W., Trok, Jared T., Wilson, Andrew J., Gould, Carlos F., Heft-Neal, Sam, Burke, Marshall, Diffenbaugh, Noah S.

Issue&Volume: 2025-12-16

Abstract: Understanding the mortality effects of the most extreme heat events is central to climate change risk analysis and adaptation decision-making. Accurate representation of these impacts requires accounting for the effects of prolonged sequences of hot days on mortality, the change in that mortality due to anthropogenic forcing, and the potential compensating effects of adaptation to heat. Here, we revisit the August 2003 heat wave in France, a canonical event in a region with rich climate and mortality data, to understand these influences. We find that standard heat–mortality exposure–response functions underpredict excess deaths in August 2003 by 55% but that accounting for the temporally compounding effects of hot days better matches observed mortality. After accounting for compounding effects and applying a machine learning approach to single-event climate attribution, we attribute 6,079 deaths in August 2003 to climate change. Finally, we show that recent adaptation to heat in France has reduced the projected death tolls of future 2003-like events by more than 75%.

DOI: 10.1073/pnas.2503577122

Source:https://www.pnas.org/doi/abs/10.1073/pnas.2503577122