Journal cover Journal topic
Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 3.102
IF3.102
IF 5-year value: 3.284
IF 5-year
3.284
CiteScore value: 5.1
CiteScore
5.1
SNIP value: 1.37
SNIP1.37
IPP value: 3.21
IPP3.21
SJR value: 1.005
SJR1.005
Scimago H <br class='widget-line-break'>index value: 90
Scimago H
index
90
h5-index value: 42
h5-index42
Preprints
https://doi.org/10.5194/nhess-2020-115
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2020-115
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  23 Apr 2020

23 Apr 2020

Review status
A revised version of this preprint is currently under review for the journal NHESS.

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 Welker1, Thomas Röösli2,3, and David N. Bresch2,3 Christoph Welker et al.
  • 1GVZ Gebäudeversicherung Kanton Zürich, Zurich, Switzerland
  • 2Institute for Environmental Decisions, ETH Zurich, Zurich, Switzerland
  • 3Federal Office of Meteorology and Climatology MeteoSwiss, Zurich, Switzerland

Abstract. With access to claims, insurers have a long tradition of being knowledge leaders on damages caused by e.g. 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: the 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 assessing rare events, such as a 250-year return period windstorm causing CHF 75 million damages. Our study emphasises 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.

Christoph Welker et al.

Interactive discussion

Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
[Login for Authors/Editors] [Subscribe to comment alert] Printer-friendly Version - Printer-friendly version Supplement - Supplement

Christoph Welker et al.

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

Christoph Welker et al.

Viewed

Total article views: 517 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
404 102 11 517 23 24
  • HTML: 404
  • PDF: 102
  • XML: 11
  • Total: 517
  • BibTeX: 23
  • EndNote: 24
Views and downloads (calculated since 23 Apr 2020)
Cumulative views and downloads (calculated since 23 Apr 2020)

Viewed (geographical distribution)

Total article views: 414 (including HTML, PDF, and XML) Thereof 414 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 29 Sep 2020
Publications Copernicus
Download
Short summary
How representative are local building insurers' claims to assess winter windstorm risk? In our case study of Zurich (CH), we use a risk model for windstorm building damages and compare three different inputs: insurance claims, 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.
How representative are local building insurers' claims to assess winter windstorm risk? In our...
Citation
Altmetrics