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Europe windstorm modeling

Europe windstorm modeling. ISCM Meeting, Zürich. Motivation. Wide divergence in expert opinions on windstorm risk. Example: loss in % of total sum insured vary by factor of 4 at 200-year return period for same portfolio. Where does the divergence comes from?.

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Europe windstorm modeling

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  1. Europe windstorm modeling ISCM Meeting, Zürich

  2. ISCM meeting, Zürich Motivation Wide divergence in expert opinions on windstorm risk. Example: loss in % of total sum insured vary by factor of 4 at 200-year return period for same portfolio.

  3. ISCM meeting, Zürich Where does the divergence comes from? • Various sources of modeling uncertainty: • Uncertainty in hazard: • Wind fields derived from observations of wind gusts, pressure maps, numerical weather prediction (NWP) models. • Frequency of events (parameter risk) • Uncertainty in vulnerability: • Standard secondary uncertainty • Loss amplifications • Other hazard parameters • Uncertainty in exposure: • Assumptions on market portfolio

  4. ISCM meeting, Zürich Uncertainty in Hazard NWP Model 1 NWP Model 2 • Reproduction of Erwin maximum gust (2005): • two NWP models and one interpolation of observations (67 points) • Large difference in wind and footprint of storm. Observed

  5. ISCM meeting, Zürich Uncertainty in event frequency • Statistical model of return periods for storm intensity: • Based on an index measuring both area and intensity of event. • Data comes from reanalysis of period 1958-2001 (ERA40) • Estimation of confidence interval • Return period for Anatol between 5 and 30 years. • Source: MeteoSwiss

  6. ISCM meeting, Zürich Loss amplification • Loss amplification has various components: • Inflation in claims size: • Increased cost of repair. • Increase in claims frequency: • behavior of policy holders • claims adjustment practices. • Very uncertain modeling: • Few events to calibrate on. • “Soft factors” are hard to quantify.

  7. ISCM meeting, Zürich Loss amplification • Difference in claims frequency as a function of wind speed for two events: • Storm 1 generated larger loss/impacted more populated area

  8. ISCM meeting, Zürich Questions for debate • What is contributing most to divergence between models? • What types of uncertainty can be/are modeled? • Are these factors specific to Europe wind? • What can we do to improve the “science” behind? • How can we best deal with divergence in expert opinions?

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