Decadal variations of European windstorms: linking research to insurance applications
Abstract. The insurance sector is affected by decadal-scale variations in annual European windstorm losses amounting to a few billion euros, yet has not applied recent advances in understanding and predicting this variability to their pricing of windstorm risk. This is mainly due to an unknown relation between insured wind losses and meteorological definitions of storminess used in research. This study aimed to reduce this uncertainty.
A history of windstorm insurance losses over the past 72 years was developed from winds in weather reanalyses. Then, typical storm proxies used by researchers, such as the North Atlantic Oscillation (NAO) and the Arctic Oscillation, were compared to the new windstorm loss record. The relationship between the proxies and losses has two distinct regimes: highly consistent from 1950 up to the 2000s, then a divergence in the past 10 to 15 years. The recent separation is large and robust, with high confidence that modern values of researchers’ proxies approach levels last seen 30 years ago, whereas decadal-mean losses are far lower today than in the 1980s and ‘90s.
The cause of this divergence was explored. Storm damages are most closely associated with peak gusts deriving their momentum from winds in the free troposphere, and pressure gradients at the surface used in typical climate indices can only partially describe higher level winds. Based on this reasoning, a new Hemispheric Geostrophy Index (HGI) was defined as the difference in 700 hPa heights between the tropics and the Arctic. It was found to vary coherently with decadal losses in the past, and crucially retains this consistency in the past 15 years too. Breaking down the HGI into component parts revealed that lower storminess in recent times is linked to ongoing reductions in poleward baroclinicity. Further development of loss history and climate indices would help bridge decadal research to insurance applications.
Status: final response (author comments only)
RC1: 'Comment on nhess-2022-268', Anonymous Referee #1, 28 Jan 2023
- AC1: 'Reply on RC1', Stephen Cusack, 17 Apr 2023
CC1: 'Comment on nhess-2022-268', Matthias Klawa, 11 Feb 2023
- AC3: 'Reply on CC1', Stephen Cusack, 17 Apr 2023
RC2: 'Comment on nhess-2022-268', Anonymous Referee #2, 13 Feb 2023
- AC2: 'Reply on RC2', Stephen Cusack, 17 Apr 2023
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This manuscript is devoted to the analysis of the recent mismatch between the interdecadal variability of storm losses in Europe, estimated from wind data using a conventional approach, and of indices of the large-scale atmospheric circulation (teleconnections), such as NAO or AO. This lack of agreement may have critical implications for insurance companies and the general population, thereby being very pertinent and within the scope of NHESS. A new hemispheric geostrophic index (HGI), based on the 700 hPa geopotential height, is then proposed as an alternative to the more conventional indices, showing a higher correlation with the recent changes in storm losses in Europe. It is argued that HGI, being closely related to the low-tropospheric thickness rather than to near-surface conditions, explains this better correspondence. Although these findings are scientifically sounding, I found some parts a bit too speculative, thus deserving a more accurate assessment and demonstration. The text is concise and clearly written. The quality of the figures can be improved. Some revision suggestions are outlined below. Hence, I recommend the publication of this manuscript after some revisions outlined below in the specific comments.
Section 2.1: please describe in greater detail the datasets and the quality of the data. The average of the two reanalysis products (ERA5 and reanalysis) is also worth explaining, preferably taking into account previous research.
Section 2.2: the use of 11-yr running means without values at the ends of the time series can also be improved using other more advanced methodologies, such as a low-pass filter with a cut-off frequency at 10 years.
Ln 104: Please specify "...to the present day".
Section 3.1: the limitations of the event loss equation are not stated, including their potential contribution to the recent bias. This is a very important aspect to discuss.
Sections 3.2 and 3.3: an assessment of the statistical significance of the trends and divergence is essential. For instance, the statements in Ln 142-143, 161-162 and 207-208 are very vague and need to be proved using robust statistical analysis of trends and inversion points.
Ln 231-232 seems to contradict the use of a zonal/hemispheric index. Please clarify.
The last paragraph of section 4.2 deserves a better discussion, including a more detailed analysis and discussion. Please revise.