Abstract

The combined effect of above-normal nighttime temperatures with high humidity poses a high risk to human health by impeding the body’s recovery from daytime heat exposure. Seasonal predictions of nighttime heat waves (NHWs) can help to better anticipate these episodes and reduce their social and economic impacts. However, the ability of the seasonal forecast systems to predict NHWs has not been explored yet. This work investigates the potential of four seasonal forecasting systems and a multi-model (MM) ensemble to provide useful information on the frequency and magnitude of the NHWs in the Euro-Mediterranean region during the boreal summer season. The analysis employs a modified version of the heat wave magnitude index (HWMI) to evaluate the NHWs. Our results demonstrate for the first time that this index is an optimal choice for the seasonal prediction analysis as it is invariant to the mean biases and provides an integrated view of the NHWs for the entire season. In addition, the percentage of days in a season with temperatures exceeding the 90th percentile (NDQ90) has been used to assess the NHWs’ seasonal frequency. Different proxies for the assessment of NHWs have been considered: apparent temperature at night (ATn, computed from temperature and humidity at night), mean temperature at night, and daily minimum temperature. All these proxies are valid for the assessment of the NHWs, but ATn is more informative about the stress on human health since it includes the impact of humidity. This work has revealed that state-of-the-art seasonal forecast systems can represent the interannual variability of both HWMI and NDQ90 in Southern Europe, Eastern Europe, and the Middle East, but they show limitations in Northern Europe. The predictive capabilities of the seasonal forecasts in specific regions demonstrate the potential of these predictions for the effective management of the risks associated with summer NHWs.

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