Abstract

<p>                Heat waves have important impacts on society and our environment. In Europe for instance, the summer of 2003 caused upwards of 40000 fatalities. They also impact the crop production, ecosystems, and infrastructures. In a warming climate, heat wave intensity and frequency are likely to increase with potentially more dramatic consequences.</p><p>                Considering this, it is crucial to forecast such extreme events and therefore gain a better understanding of their triggering processes. The determination of these processes requires to identify heat wave patterns (timing and location) together with the correlated large-scale circulation patterns. This will enable to devise early warning systems, that could help mitigate the impact.</p><p>                This work is part of an ongoing PhD project focusing on improving the forecast of heat waves at sub-seasonal time scale. The main objectives are to evaluate the link between large scale weather patterns and severe warm events over Europe and measure current level of predictive skill. The first part will focus on defining an objective criteria to identify heat wave events in the ERA5 reanalaysis dataset from ECMWF. The identification of heat waves depends on three main criteria: temperature threshold, spatial and temporal extension. Meaning that the temperature should exceed a defined threshold over a large enough region and for a long enough period. We will consider daily means as well as maximum and minimum values of 2m temperature. We will identify the circulation patterns (persistent high pressure systems) associated with heat wave events and analyse the key differences with persistent high pressure systems that are not associated with heat waves.</p><p>                <strong>This work is part of the Climate Advanced Forecasting of sub-seasonal Extremes (CAFE) project, funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grand agreement No 813844</strong>.</p>

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