1. Windstorms and Insurance RMetS Student Conference 21-23 August 2006 Richard Hewston r.hewston@uea.ac.uk University of East Anglia http://www.uea.ac.uk/~e470848/ Supervisors: Dr Stephen Dorling Dr David Viner Funding: Worshipful Company of Insurers

2. Worldwide Natural Catastrophes Increasing economic and insured loss Since 1970, of the most expensive 40 insured losses, 33 were weather related with 29 windstorm related. Successive record annual insured losses in 2004 and 2005 Successive record annual insured losses in 2004 and 2005

3. Worldwide Natural Catastrophes Increasing economic and insured loss Since 1970, of the most expensive 40 insured losses, 33 were weather related with 29 windstorm related. Successive record annual insured losses in 2004 and 2005 Successive record annual insured losses in 2004 and 2005 The trend exhibited is influenced by economic and demographic shifts and well as natural factors.

4. Weather Related Insured Loss in the UK ~30% of loss from subsidence ~30% of loss from subsidence ~70% associated with storms ~70% associated with storms *Jan-June 2005 only

5. Weather Related Insured Loss in the UK ~30% of loss from subsidence ~30% of loss from subsidence ~70% associated with storms ~70% associated with storms *Jan-June 2005 only Domestic claims make up 70-85% of total losses Business Interruption accounts for ~12% of commercial claims (~3% of total weather related insured loss)

6. Weather Related Insured Loss in the UK 4 th quarter 2000 - Wettest Autumn for more than 200 years

7. Weather Related Insured Loss in the UK 4 th quarter 2000 - Wettest Autumn for more than 200 years 1 st quarter 2005 due largely to windstorm Erwin

8. Windstorm Erwin Wind at altitude of 9km for 1800GMT on 7th January, 2005 Source: Danish Met Institute

9. Windstorm Erwin Insured losses Insured losses UK ~£250m UK ~£250m Denmark ~£400m Denmark ~£400m Sweden ~£230m Sweden ~£230m Sweden recorded windspeeds of 33m/s inland, resulting in unprecedented damage to the forest industry (£1.6-2.3bn) Sweden recorded windspeeds of 33m/s inland, resulting in unprecedented damage to the forest industry (£1.6-2.3bn) Industry wide, the figure for total insured losses relating to Windstorm Erwin stands at £1.1bn Industry wide, the figure for total insured losses relating to Windstorm Erwin stands at £1.1bn Wind at altitude of 9km for 1800GMT on 7th January, 2005 Source: Danish Met Institute

10. Modelling Windstorm Loss Crichton, D. (1999). The Risk Triangle, Natural Disaster Management. Journal, Ingleton. London, Tudor Rose: 102-103. Risk Triangle Source: Crichton (1999) Exposure – position, orientation, regional terrain, topography Vulnerability - shape, constructional details and state of maintenance (preparedness) Hazard – windstorm characteristics

11. Modelling Windstorm Loss Crichton, D. (1999). The Risk Triangle, Natural Disaster Management. Journal, Ingleton. London, Tudor Rose: 102-103. Windstorm damage is the result of wind loads exceeding the resistance of the structure, affecting parts of the building such as roofs, envelopes and openings. 79% of all damage since 1970 is related to roofs Important factor is Vulnerability Different regions have different building standards Risk Triangle Source: Crichton (1999) Exposure – position, orientation, regional terrain, topography Vulnerability - shape, constructional details and state of maintenance (preparedness) Hazard – windstorm characteristics

12. Modelling Windstorm Loss Following Klawa and Ulrbich (2003) Following Klawa and Ulrbich (2003) Windstorm loss modelling using Windstorm loss modelling using wind gust speeds from a network of UK Met Office observing stations wind gust speeds from a network of UK Met Office observing stations various socioeconomic data sets which help to quantify vulnerability various socioeconomic data sets which help to quantify vulnerability Claims data from insurers for verification Claims data from insurers for verification Klawa, M and U. Ulbirch (2003), A Model for the Estimation of Storm Losses and the Identification of Severe Winter Storms in Germany, Natural Hazards and Earth Systems Sciences, Vol. 3, pp725-732

13. Modelling Windstorm Loss Maximum windspeeds, not mean windspeeds, closely related to damage (eg.Dorland et al (2000), Hanson et al (2004)). Maximum windspeeds, not mean windspeeds, closely related to damage (eg.Dorland et al (2000), Hanson et al (2004)). Daily maximum gust speed and direction are available from the British Atmospheric Data Centre Daily maximum gust speed and direction are available from the British Atmospheric Data Centre The 98th percentile value of the daily maximum gust speeds used, incorporating “wind climate” The 98th percentile value of the daily maximum gust speeds used, incorporating “wind climate” 98 th percentile Maximum Gust Speeds Dorland, K., J. Palutikof and R. Tol (2000). Modelling Storm Damage in the Netherlands and the UK., in Weather Impacts on Natural, Social and Economic Systems in the Netherlands. Institute for Environmental Studies, Vrije Universiteit, Amsterdam: 57-81. Hanson, C., T. Holt and J. Palutikof (2004). An Integrated Assessment of the potential for Change in Storm Activity over Europe: Implications for Insurance and Forestry in the UK. Norwich, Tyndall Centre: 98. Wind Data

14. Modelling Windstorm Loss Socio-economic Data Census data from 1981,1991 and 2001 Census data from 1981,1991 and 2001 Experian data  “Wealth indicators” Experian data  “Wealth indicators” Household Density (2000)

15. Modelling Windstorm Loss Claims Data Ecclesiastical Insurance Group Ecclesiastical Insurance Group Norwich Union (via loss adjustors Cunningham Lindsey) Norwich Union (via loss adjustors Cunningham Lindsey) Claims data for domestic properties suffering losses associated from windstorm Claims data for domestic properties suffering losses associated from windstorm

16. Modelling Windstorm Loss Claims Data Ecclesiastical Insurance Group Ecclesiastical Insurance Group Norwich Union (via loss adjustors Cunningham Lindsey) Norwich Union (via loss adjustors Cunningham Lindsey) Claims data for domestic properties suffering losses associated from windstorm Claims data for domestic properties suffering losses associated from windstorm Claims Associated with Windstorm Erwin (Jan 2005)

17. Modelling Windstorm Loss Windstorm Erwin Max Gust Speeds (normalised to 98 th percentile value)

18. Modelling Windstorm Loss Windstorm Erwin Predicted insured loss

19. Modelling Windstorm Loss Windstorm Erwin Predicted insured lossActual insured loss

20. Climate Change and Future Losses Crichton, D. (1999). The Risk Triangle, Natural Disaster Management. Journal, Ingleton. London, Tudor Rose: 102-103. Dlugolecki, A. (2004). A Changing Climate for Insurance - A summary report for Chief Executives and Policymakers, Association of British Insurers. Risk Triangle Source: Crichton (1999) Climate change Climate change  Change in Hazard  Change in Hazard ABI believe we are currently seeing an annual increase in losses of 2-4% due to climate change (Dlugolecki 2004) Damage functions NOT a linear relationship to weather hazard (eg. Wind Damage is related to cube of wind speed)

21. Climate Change and Future Losses Using RCM output in the loss model to simulate future losses

22. Climate Change and Future Losses Using RCM output in the loss model to simulate future losses Providing REgional Climates for Impacts Studies (PRECIS) driven by ECMWF 40 Year Re-analysis (ERA-40) data for 25km grid hourly data for 25km grid

23. Climate Change and Future Losses Using RCM output in the loss model to simulate future losses Providing REgional Climates for Impacts Studies (PRECIS) driven by ECMWF 40 Year Re-analysis (ERA-40) data at 25km 2 hourly data at 25km 2 Run PRECIS with boundary conditions from HadAM3P (2070-2100) Max Planck Institute ECHAM4 global climate model Run PRECIS under different IPCC Special Report on Emissions Scenarios (SRES)

24. Thank You