Preprints
https://doi.org/10.5194/nhess-2024-16
https://doi.org/10.5194/nhess-2024-16
28 Feb 2024
 | 28 Feb 2024
Status: this preprint is currently under review for the journal NHESS.

Insurance loss model vs meteorological loss index – How comparable are their loss estimates for European windstorms?

Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto

Abstract. Windstorms affecting Europe are among the natural hazards with the largest socio-economic impacts. Therefore, many sectors like society, economy or the insurance industry are highly interested in reliable information on associated impacts and losses. There are different metrics to quantify windstorm-related losses, ranging from simple natural hazard databases over loss indices based on meteorological variables to more complex insurance loss (catastrophe) models. In this study, we compare estimated windstorm losses using the meteorological Loss Index (LI) with losses obtained from the European Windstorm Model of Aon Impact Forecasting. To test the sensitivity of LI to different meteorological input data, we furthermore contrast LI based on the reanalysis dataset ERA5 and its predecessor ERA-Interim. We focus on similarities and differences between the datasets in terms of loss values and storm rank for specific storm events in the common reanalysis period across 11 European countries.

Our results reveal higher LI values for ERA5 than for ERA-Interim for all of Europe, coming mostly from a higher spatial resolution in ERA5. The storm ranking is comparable for Western and Central European countries for both reanalyses. Compared to Aon’s Impact Forecasting model, LI ERA5 shows comparable storm ranks. However, LI seems to have difficulties in distinguishing between extreme windstorms with high losses and those with only moderate losses. The loss distribution in LI is thus not steep enough and the tail is probably on the short side, yet it is an effective index, precisely because of its simplicity, suitable for estimating the impacts and ranking storm events.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2024-16', Gerard van der Schrier, 29 Mar 2024
    • AC1: 'Reply on RC1', Julia Moemken, 07 Jun 2024
  • CC1: 'Comment on nhess-2024-16', Mathias Raschke, 10 Apr 2024
    • AC4: 'Reply on CC1', Julia Moemken, 07 Jun 2024
  • RC2: 'Comment on nhess-2024-16', Anonymous Referee #2, 16 Apr 2024
    • AC2: 'Reply on RC2', Julia Moemken, 07 Jun 2024
  • RC3: 'Comment on nhess-2024-16', Anonymous Referee #3, 26 Apr 2024
    • AC3: 'Reply on RC3', Julia Moemken, 07 Jun 2024
  • CC2: 'Comment on nhess-2024-16', Irene Garcia-Marti, 06 Jun 2024
    • AC5: 'Reply on CC2', Julia Moemken, 07 Jun 2024
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto
Julia Moemken, Inovasita Alifdini, Alexandre M. Ramos, Alexandros Georgiadis, Aidan Brocklehurst, Lukas Braun, and Joaquim G. Pinto

Viewed

Total article views: 750 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
528 175 47 750 52 24 28
  • HTML: 528
  • PDF: 175
  • XML: 47
  • Total: 750
  • Supplement: 52
  • BibTeX: 24
  • EndNote: 28
Views and downloads (calculated since 28 Feb 2024)
Cumulative views and downloads (calculated since 28 Feb 2024)

Viewed (geographical distribution)

Total article views: 714 (including HTML, PDF, and XML) Thereof 714 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 22 Jul 2024
Download
Short summary
European windstorms regularly cause damage to natural and human-made environments, leading to high socio-economic losses. For the first time, we compare estimates of these losses using a meteorological Loss Index (LI) and the insurance loss (catastrophe) model of Aon Impact Forecasting. We find that LI underestimates high impact windstorms compared to the insurance model. Nonetheless, due to its simplicity, LI is an effective index, suitable for estimating impacts and ranking storm events.
Altmetrics