Dr Luca Famooss Paolini
Universita Di Bologna
Enhancing seasonal forecast of heat stress indicators through teleconnection-based subsampling
Recent studies show that summer heat extremes over Europe have increased since the mid-20th century and are projected to intensify with ongoing global warming (Seneviratne et al., 2021). Thus, predicting these events months in advance is critical due to their socio-economic and environmental impacts. However, state-of-the-art dynamical seasonal prediction systems (SPSs) still show limited skill in forecasting European heat extremes, especially over central and northern Europe (Prodhomme et al., 2022). Interestingly, recent studies have shown that our skills in predicting extratropical climate can be largely improved by subsampling the dynamical SPS ensemble with statistical post-processing techniques (Dobrynin et al., 2022).
Based on these pieces of evidence, I will present an application of the teleconnection-based subsampling to improve the seasonal prediction of summer climate and extreme temperatures over Europe. This approach is applied to the multi-model ensemble (MME) of SPSs contributing to the Copernicus Climate Change Service (C3S), analysing the hindcast period 1993–2016. The MME is subsampled by retaining only those ensemble members that properly capture the teleconnections between the most important weather regimes of the North Atlantic sector (i.e. North Atlantic Oscillation and Eastern Atlantic pattern) and their respective spring predictors (Famooss Paolini et al., 2025).
Finally, I will discuss ongoing developments from my short-term visit at ECMWF, where the teleconnection-based subsampling approach will be tested in an operational environment to improve the seasonal prediction of health-related indicators.