1,252
Views
20
CrossRef citations to date
0
Altmetric
Dynamic meteorology

Modelling economic losses of historic and present-day high-impact winter windstorms in Switzerland

, , , , &
Article: 29546 | Received 27 Aug 2015, Accepted 01 Mar 2016, Published online: 30 Mar 2016
 

Abstract

This study investigates the wind gusts and associated economic loss patterns of high-impact winter windstorms in Switzerland between 1871 and 2011. A novel approach for simulating windstorm-related gusts and losses at regional to local scales is applied to a sample of 84 windstorms. The approach involves the dynamical downscaling of the Twentieth Century Reanalysis (20CR) ensemble mean to 3-km horizontal grid size using the Weather Research and Forecasting (WRF) model. Economic losses are simulated at municipal level for present-day asset distribution based on the downscaled (parameterised) wind gusts at high spatiotemporal resolution using the open-source impact model climada. A comparison with insurance loss data for two recent windstorms (“Lothar” in 1999, “Joachim” in 2011) indicates that the loss simulation allows to realistically simulate the spatial patterns of windstorm losses. The loss amplitude is strongly underestimated for ‘Lothar’, while it is in reasonable agreement for ‘Joachim’. Possible reasons are discussed. Uncertainties concerning the loss simulation arise from the wind gust estimation method applied; estimates can differ considerably among the different methods, in particular over high orography. Furthermore, the quality of the loss simulation is affected by the underlying simplified assumptions regarding the distribution of assets and their susceptibilities to damage. For the whole windstorm sample, composite averages of simulated wind gust speed and loss are computed. Both composites reveal high values for the densely populated Swiss Plateau and lower values for south-eastern Switzerland; metropolitan areas stand out in the loss composite. Eight of the top 10 events concerning the losses simulated for present-day asset distribution and summed over all Swiss municipalities occurred after 1950. It remains uncertain whether this is due to decadal-scale changes of winter windstorms in Switzerland or merely due to a possible bias of the 20CR ensemble mean towards lower wind speeds in the period before around 1950.

To access the supplementary material to this article, please see Supplementary files under ‘Article Tools’.

To access the supplementary material to this article, please see Supplementary files under ‘Article Tools’.

7. Acknowledgements

We are very thankful to the Swiss Mobiliar and the Intercantonal Reinsurance for providing insurance loss data. Support was provided by Meteotest, the Swiss Federal Office for the Environment, MeteoSwiss, and the Dr. Alfred Bretscher Fonds. Support for the Twentieth Century Reanalysis Project dataset is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and the National Oceanic and Atmospheric Administration Climate Program Office.

Notes

To access the supplementary material to this article, please see Supplementary files under ‘Article Tools’.