More than 110,000 Europeans died as a result of the record-breaking temperatures of 2022 and 2023. A new generation of impact-based early warning systems, using epidemiological models to transform weather forecasts into health forecasts for targeted population subgroups, is an essential adaptation strategy to increase resilience against climate change. Here, we assessed the skill of an operational continental heat-cold-health forecasting system. We used state-of-the-art temperature-lag-mortality epidemiological models to transform bias-corrected ensemble weather forecasts into daily temperature-related mortality forecasts. We found that temperature forecasts can be used to issue skillful forecasts of temperature-related mortality. However, the forecast skill varied by season and location, and it was different for temperature and temperature-related mortality due to the use of epidemiological models. Overall, our study demonstrates and quantifies the forecast skill horizon of heat-cold-health forecasting systems, which is a necessary step toward generating trust among public health authorities and end users.

中文翻译：

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运行中的大陆热-冷-健康预报系统的预报技能评估：健康预警系统的新途径


超过 110,000 名欧洲人死于 2022 年和 2023 年破纪录的气温。新一代基于影响的早期预警系统使用流行病学模型将天气预报转化为目标人群亚群的健康预报，是提高对气候变化的抵御能力的重要适应策略。在这里，我们评估了运行中的大陆热-冷-健康预报系统的技能。我们使用最先进的温度-滞后-死亡率流行病学模型将偏差校正的集成天气预报转换为每日与温度相关的死亡率预报。我们发现温度预报可用于发布与温度相关的死亡率的巧妙预测。然而，预报技能因季节和地点而异，由于使用了流行病学模型，温度和温度相关死亡率也不同。总体而言，我们的研究演示并量化了热-冷-健康预测系统的预测技能范围，这是在公共卫生当局和最终用户之间建立信任的必要步骤。