Case study: Insurance

Insurance

European Windstorms are one of the key hazards for the insurance industry. WINDSURFER is contributing new knowledge to help the insurance industry risk assessments. Key knowledge gaps that WINDSURFER is addressing include:

The clustering of windstorms
Understanding past windstorm events

Windstorm Clustering

WINDSURFER outcomes involves new studies on the impact of windstorm clustering on insurance related losses. European windstorms are not random, and tend to group together in clusters. Using climate model outputs, Priestly et al. (2018) have recently shown that clustering increases the 1-in-200 year annual windstorm risk by 10-20%.

Historical Windstorms

WINDSURFER has been investigating how windstorms have varied over the 20th Century. One recent study (Bloomfield et al. 2018) has shown that we still know very little about how intense storms in the early 20th century, and that we need to cautious about interpreting trends from some of the latest atmospheric renanalysis.

Engaging with the insurance industry: Scientists from WINDSURFER have been presenting their work at a range of different industry events including the 2017 and 2018 OASIS Loss Modelling Conferences and the 2017 and 2018 European Windstorm Workshops. We've also been engaging with insurance and reinsurnce companies on a one-to-one basis. If your interested in learning more about the datasets and science outcomes from WINDSURFER then contact Len Shaffrey at L.C.Shaffrey@reading.ac.uk.

References

Bloomfield, H. C., Shaffrey, L. C., Hodges, K. I. and Vidale, P. L. (2018) A critical assessment of the long term changes in the wintertime surface Arctic Oscillation and Northern Hemisphere storminess in the ERA20C reanalysis. Environmental Research Letters, 13 (9). 094004. ISSN 1748-9326 doi: https://doi.org/10.1088/1748-9326/aad5c5

Priestley, M. D. K., Dacre, H. F., Shaffrey, L. C., Hodges, K. I. and Pinto, J. G. (2018) The role of serial European windstorm clustering for extreme seasonal losses as determined from multi-centennial simulations of high resolution global climate model data. Natural Hazards and Earth System Science, 18. pp. 2991-3006. ISSN 1684-9981 doi: https://doi.org/10.5194/nhess-18-2991-2018

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