A methodology for attributing extreme extratropical cyclones to climate change: the case study of storm Alex 2020

Extreme event attribution aims at evaluating the impact of climate change on specific extreme events. In this work, we present an attribution methodology for extreme extratropical cyclones, and test it on storm Alex. This storm was an explosive extratropical cyclone that affected Southern France and Northern Italy at the beginning of October 2020. The methodology exploits mathematical properties of circulation analogues, and determines changes in physical and statistical properties. We first divide 6-hourly ERA5 data into two periods: a counterfactual period with a weak climate change signal (1950-1984) and a factual period with a strong climate change signal (1986-2021). We then identify the 30 cyclones in each period whose sea-level pressure maps are closer to Alex's map . We term these "analogues" of Alex. We find that analogues in the factual period are more persistent than in the counterfactual period, which may favour more severe impacts resulting from persistent strong winds and heavy precipitation, as was the case for Alex. This effect is compounded by the doubling in accumulated daily precipitation detected in Northern Italy between the counterfactual and factual analogues. In the factual period, the analogues also display deeper cyclones with poleward-shifted tracks. We also identify a seasonal shift of the analogues, from spring to autumn. Finally, the analogues in the factual world are closer to Alex than in the counterfactual. These changes collectively point that high-impact storms like Alex have become more common in a changing climate. We are currently extending the analysis using CMIP6 models and present here some preliminary results.