Forecast skill assessment of an operational continental heat-cold-health forecasting system: New avenues for health early warning systems

Abstract

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.