Dear authors,

I am very interested in any kind of quantification of aggregated natural catastrophes (natcat) losses from such as you present, as I am employed in (re)insurance industry for natcat modelling and research and publish as freelancer in this field. Unfortunately, I realize many gaps and shortfalls in and questions regarding your draft about event losses from windstorms (in parts of Europe):

• Why is the renaming (storm severity index [SSI] to meteorological loss index [LI]) not mentioned in the abstract?
• As far as I know, the original purpose of the SSI was not to estimate loss, but to formulate a size measure (for spatial extent (RMS 2024)). The SSI is also used to quantify spatial correlation (Bonazzi et al. 2012).What means a “metrics to quantify windstorm-related losses”? An event loss can be recorded or estimated. Why so you change this focus?
• The natcat models in (re)insurance industry (such as the applied Aon’s IF Euro WS model) are less explained in the draft  in contrast to your reference Mitchell-Wallace et al. (2017). Alternative models and vendors are not even mentioned. The Natcat model with thousands of stochastic events estimates event losses for a defined exposure and (high) return period.
• What sense does it make to compare two model results on event losess when data for (insured) event losses and corresponding exposure (provided by the Perils AG, mentioned in your draft) are available? There is also information about market penetration (proportion of insured exposure to insurable exposure).
• Why is my model (Raschke 2022) not even mentioned? The agreement between estimated and observed event damage (windstorm Germany) is significantly better in my results (plot) than in yours.
• The loss/damage function applied should be discussed. The power parameter of 3 might be unrealistic. The wind speed does not cause damage, but rather it creates a damage generating wind pressure/load (at the buildings) that is proportional to the squared wind speed (details see Raschke 2022).
• Correlation measures has been formulated for random variables. The maximum event loss per year or the annual sum of such losses are random variables (drawn once per year). However, event losses don’t be random variables but point events of a stochastic process. Therefore, you can't just apply a correlation measure to it.

Besides, the results are not perfectly presented (e.g., Figure 8, colour scale for correlation measure form blue [-0.9] to red [0.9] although only positive correlations are mapped).

With kind regards,

Mathias Raschke

References

Bonazzi, A. et al. The spatial structure of European wind storms as characterized by bivariate extreme-value Copulas. Nat. Hazards Earth Syst. Sci. 12, 1769–1782 (2012).

Natural Catastrophes – Risk Management and Modelling – A Practioner’s Guide (eds Mitchell-Wallace, K. et al.) (Wiley Blackwell, 2017).

Raschke, M. About the return period of a catastrophe. Nat. Hazards Earth Syst. Sci. 22, 245–263 (2022).

RMS Verisk. Storm Severity Index (SSI), Help Centre Risk Link Storm Severity Index (SSI), (2023).

Dear authors,



Please find attached a review for the manuscript nhess-2024-16 submitted to the NHESS journal. I hope these comments will be helpful and sufficiently informative to come up with a new version of the manuscript.

Good luck and kind regards,

Irene Garcia-Marti