Climate change projections of European windstorm damages are highly uncertain because of different climate model responses and large internal variability. This study uses Generalized Linear Models and a weighted median estimation to optimally extract forced trends in a number of European windstorm metrics. Footprints of windstorms ...
Climate change projections of European windstorm damages are highly uncertain because of different climate model responses and large internal variability. This study uses Generalized Linear Models and a weighted median estimation to optimally extract forced trends in a number of European windstorm metrics. Footprints of windstorms associated with extratropical cyclones are created for an ensemble of models from the 6th Coupled Model Intercomparison Project (CMIP6) across a full transient timeseries from 1980-2100. Trends are assessed over time, but also as a function of global mean surface temperature changes. Trends in aggregate severity are attributed to changes in storm average severity, frequency, and area impacted, with changes in area being the dominant driver of changes to average storm severity. Confidence in the findings is assessed, with high confidence of declines in frequency for southern and northern Europe, medium confidence of an increase in average windstorm severity for parts of northwestern Europe, and low confidence of any changes for eastern Europe. A 15-member ensemble of the MPI-ESM1-2-LR model is used to assess internal variability. Trends between individual members can vary significantly, however the uncertainty due to internal variability in the 15-member ensemble is generally only 50% of that in the multi-model ensemble of CMIP6 models for aggregate severity. With largest uncertainty coming from model differences, a large proportion of uncertainty in future windstorms is therefore potentially reducible with modelling advances.
