Towards Impact-Based Forecasting of Storm-Damages Using Locally Calibrated Damage Functions

Windstorms are a significant natural hazard in Europe and Norway, and while many national meteorological agencies issue warnings for severe storm events, studies estimating their impacts are rare. It has been hypothesized that forecasting storm damages could help stakeholders make better informed decisions in the event of a storm. Using 41 years of daily municipality-level historical Norwegian insurance loss data and high resolution wind speed data from the Norwegian hindcast (NORA3), we propose a novel conceptual framework for probabilistic storm damage forecasting and we test it on the Norwegian Meteorological Institute's MetCoOp Ensemble Prediction System (MEPS). The damage forecasting is performed in two steps: first, a color-coded warning system that issues warnings based on the municipality-level probabilities of the event being a medium, high, or extreme loss event, and second, forecasting damages in monetary terms using damage functions. The color-coded warning system is implemented at the municipality level and the gridded wind speeds are weighted with population density to account for local exposure. The monetary damages are estimated on a county level using four different damage functions. The damage-informed color-coded warning system shows promising results in comparison with a more traditional wind-informed return period-based warning system, demonstrating the ability to forecast the spatial patterns of losses across different loss categories. The county-specific recorded damages lie within the range of the ensemble of damage forecasts 70% of the time for storms not used in the fitting of the damage functions. However, the proposed color-coded warning for damage forecasting is not free from false alarms but is suited to act as a decision help for skilled users.