Using high-resolution global climate models from the PRIMAVERA project to create a European winter windstorm event set

Abstract

PRIMAVERA (process-based climate simulation: advances in high-resolution modelling and European climate risk assessments) was a European Union Horizon 2020 project whose primary aim was to generate advanced and well-evaluated high-resolution global climate model datasets for the benefit of governments, business and society in general. Following consultation with members of the insurance industry, we have used a PRIMAVERA multi-model ensemble to generate a European winter windstorm event set for use in insurance risk analysis, containing approximately 1300 years of windstorm data. The data are available at https://doi.org/10.5281/zenodo.6492182. To create the storm footprints for the event set, the storms in the PRIMAVERA models are identified through tracking. A method is developed to separate the winds from storms occurring in the domain at the same time. The wind footprints are bias corrected and converted to 3 s gusts onto a uniform grid using quantile mapping. The distribution of the number of model storms per season as a function of estimated loss is consistent with re-analysis, as are the total losses per season, and the additional event set data greatly reduce uncertainty on return period magnitudes. The event set also reproduces the temporally clustered nature of European windstorms. Since the event set is generated from global climate models, it can help to quantify the non-linear relationship between large-scale climate indices such as the North Atlantic Oscillation (NAO) and windstorm damage. Although we find only a moderate positive correlation between extended winter NAO and storm damage in northern European countries (consistent with re-analysis), there is a large change in risk of extreme seasons between negative and positive NAO states. The intensities of the most severe storms in the event set are, however, sensitive to the gust conversion and bias correction method used, so care should be taken when interpreting the expected damages for very long return periods.