Open this publication in new window or tab >>Show others...
2025 (English)In: Earth System Science Data, ISSN 1866-3508, E-ISSN 1866-3516, Vol. 17, no 9, p. 4431-4453Article in journal (Refereed) Published
Abstract [en]
The CLIMK–WINDS (CLimes IMK – WINDstorm) database is a new, publicly available, database of extreme European windstorm footprints for the extended winter season during 1995–2015. In contrast with previously compiled European windstorm databases, it includes storm footprints derived from four different data sets, rather than a single source: the ERA5 reanalysis, the COSMO-REA6 reanalysis for Europe, the COSMO-Climate Limited-area Mode regional climate model driven by ERA5 on the EURO-CORDEX domain and simulation output from the same model but on an enlarged Germany domain with higher horizontal resolution. The database includes the footprints themselves, expressed as the relative daily maximum wind gusts associated with a storm event, the daily maximum wind gusts in absolute magnitude associated with the footprints and a measure of storm severity. We applied a consistent methodology, the storm loss index, across input data sets for identifying storm footprints and assessing their severity. We identified and included the storm footprints associated with the 50 most severe storms, or top 50 storms, within each of the four input data sets. This enables a direct comparison between the footprints derived from the different input data sets, eases future efforts to extend the time record of the database or to include additional input data sets and enables assessment of uncertainty in the footprints. Moreover, since we derived the top 50 storms from each input data set at its native horizontal resolution, the database also allows us to characterise the impact that horizontal resolution can have on footprint identification and severity assessment. We find that the choice of input data set – including the data's horizontal resolution – can have major effects on extreme storm identification and characterisation. Different storms were identified as belonging to the top 50 storms in the different data sets, and storm footprints for common storms displayed substantial variability across the data sets. A comparison of our database with two existing windstorm databases also highlights the important role of the footprint detection methodology. The CLIMK–WINDS database thus supports both the research community and the insurance industry in exploring the data set, methodology and resolution dependence of assessments of extreme storm hazards. The data presented here can be downloaded from https://doi.org/10.5281/zenodo.10594398 (Flynn et al., 2024).
National Category
Physical Geography
Identifiers
urn:nbn:se:su:diva-248868 (URN)10.5194/essd-17-4431-2025 (DOI)001567920400001 ()2-s2.0-105022446103 (Scopus ID)
2025-11-042025-11-042025-12-02Bibliographically approved