Enhanced C3S Windstorm Service: A Novel Dataset of European Extratropical Cyclone Windstorms Based on ERA5 Reanalysis

Extratropical cyclones (ETCs) are dominant meteorological structures playing a crucial role in midlatitudes climate. ETCs are also responsible for heavy precipitation events, strong surface winds and wind gusts exposing populations to hazards and causing widespread and significant damages. The response of ETCs to a warming atmosphere is characterized by substantial uncertainty. This arises primarily from two key factors: significant inter-annual variability, which complicates trend detection, and the interplay of non-linear and potentially compensating mechanisms, which render future changes in the ETC climate challenging to evaluate, understand and predict. Additionally, North Atlantic ETC trend evaluation and understanding crucially depend on methodological analysis choices regarding datasets (e.g., observations, reanalysis, proxies, model simulations and analysis period) and approaches to examine storm features (i.e., Eulerian vs. Lagrangian).

Here, we present and preliminarily evaluate a novel dataset of European windstorms associated with ETCs based on the whole ERA5 reanalysis period (1940-present). This dataset is produced within the Copernicus Climate Change Service (C3S) Enhanced Operational Windstorm Service (EWS), to promote a knowledge-based assessment of the nature and temporal evolution of European windstorms associated with ETC. Such a dataset is primarily thought to provide high-quality, standardized data on windstorms which support various industrial sectors, particularly insurance and risk management, by offering insights into the intensity, frequency, vulnerability and impact of windstorms. EWS includes two datasets: windstorm tracks, based on two tracking algorithms (TRACK and TempestExtremes), and windstorm footprints, produced considering both original-resolution ERA5 variables and statistically downscaled ERA5 variables, with a target grid at 1 km resolution.

A preliminary analysis of the datasets shows increasing trends of cold-semester windstorm frequency and of the associated footprint magnitude over a portion of the European territory. The choice of the tracking algorithm is shown to be an important factor in the analysis process, as it results in non-negligible uncertainties in main windstorm statistics.