Matteo De Felice , Laurent Dubus , Emma Suckling, Alberto Troccoli

In this paper we analyse and quantify the impact of North Atlantic Oscillation (NAO) on the daily hydropower generation in the European countries. We create a consistent dataset of hydropower generation using a machine- learning methodology, this activity is an output of the Copernicus Climate Change Service ECEM contract. The model is set up using generation data on 2015-2016, and then an artificial dataset was built over the period 1979- 2017, as if the installed capacity, that of 2017, had been the same all along the period, using reanalysis data for the meteorological variables. This synthetic dataset thus generated has been used to analyse the changes in national hydro-power generation (both for run-of-river and reservoir-based plants) be- tween years when NAO is positive and when it is negative, over Europe. The results show how the majority of countries in southern Europe experience a reduction in generation during NAO positive phases. In particular the Iberian peninsula shows a clear sensitivity with change of both the hydro-power generation typologies in the range -8% – -4% in terms of capacity factor. This work also shows the benefit of having a pan-European dataset of energy vari- ables spanning multiple decades to analyse the impact of climate phenomena on the European energy sector.