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

Welker, Christoph; Röösli, Thomas; Bresch, David N.

doi:https://doi.org/10.5194/nhess-21-279-2021

Articles | Volume 21, issue 1

https://doi.org/10.5194/nhess-21-279-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-21-279-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 21, issue 1

Research article

|

25 Jan 2021

Research article |

| 25 Jan 2021

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

Christoph Welker, Thomas Röösli, and David N. Bresch

Data sets

Probabilistic Windstorm Hazard Event Set for Europe T. Röösli and D. N. Bresch https://doi.org/10.3929/ethz-b-000406567

Model code and software

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

CLIMADA_python documentation G. Aznar-Siguan and D. N. Bresch https://climada-python.readthedocs.io/en/stable/

ThomasRoosli/climada_papers_winter_windstorms_model: Winter windstorm model T. Röösli, C. Welker, and D. N. Bresch https://doi.org/10.5281/zenodo.4442602

CLIMADA-python D. N. Bresch and G. Aznar-Siguan https://github.com/CLIMADA-project/climada_python

CLIMADA_python documentation G. Aznar-Siguan and D. N. Bresch https://climada-python.readthedocs.io/en/stable/

Short summary

How representative are local building insurers' claims to assess winter windstorm risk? In our case study of Zurich, we use a risk model for windstorm building damages and compare three different inputs: insurance claims and historical and probabilistic windstorm datasets. We find that long-term risk is more robustly assessed based on windstorm datasets than on claims data only. Our open-access method allows European building insurers to complement their risk assessment with modelling results.