Comparing an insurer's perspective on building damages with modelled damages from pan-European winter windstorm event sets: a case study from Zurich, Switzerland

Author:

Welker ChristophORCID,Röösli ThomasORCID,Bresch David N.ORCID

Abstract

Abstract. With access to claims, insurers have a long tradition of being knowledge leaders on damages caused by windstorms. However, new opportunities have arisen to better assess the risks of winter windstorms in Europe through the availability of historic footprints provided by the Windstorm Information Service (Copernicus WISC). In this study, we compare how modelling of building damages complements claims-based risk assessment. We describe and use two windstorm risk models: an insurer's proprietary model and the open source CLIMADA platform. Both use the historic WISC dataset and a purposefully built, probabilistic hazard event set of winter windstorms across Europe to model building damages in the canton of Zurich, Switzerland. These approaches project a considerably lower estimate for the annual average damage (CHF 1.4 million), compared to claims (CHF 2.3 million), which originates mainly from a different assessment of the return period of the most damaging historic event Lothar–Martin. Additionally, the probabilistic modelling approach allows assessment of rare events, such as a 250-year-return-period windstorm causing CHF 75 million in damages, including an evaluation of the uncertainties. Our study emphasizes the importance of complementing a claims-based perspective with a probabilistic risk modelling approach to better understand windstorm risks. The presented open-source model provides a straightforward entry point for small insurance companies.

Publisher

Copernicus GmbH

Subject

General Earth and Planetary Sciences

Reference60 articles.

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2. Aznar-Siguan, G. and Bresch, D. N.: CLIMADA_python documentation, https://climada-python.readthedocs.io/en/stable/ (last access: 17 July 2019), 2019b.

3. Bresch, D. N.: Shaping Climate Resilient Development – Economics of Climate Adaptation, in: Climate Change Adaptation Strategies – An Upstream-downstream Perspective, edited by: Salzmann, N., Huggel, C., Nussbaumer, S., and Ziervogel, G., Springer, Cham, 241–254, https://doi.org/10.1007/978-3-319-40773-9_13, 2016.

4. Bresch, D. N. and Aznar-Siguan, G.: CLIMADA-python, available at: https://github.com/CLIMADA-project/climada_python (last access: 17 July 2019), 2019a.

5. Bresch, D. N., Aznar Siguan, G., Bozzini, V., Bungener, R., Eberenz, S., Hartman, J., Mühlhofer, E., Pérus, M., Röösli, T., Sauer, I., Schmid, E., Stalhandske, Z., Steinmann C., and Stocker, D.: CLIMADA_python v1.4.1, https://doi.org/10.5905/ethz-1007-252, 2020.

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