12B.3
Hurricane Risk Evaluation Using a Stochastically Simulated Event Set of Tropical Cyclone Tracks
Helga Weindl, Munich Reinsurance Company, 80796, Munich, Germany; and J. Rumpf, V. Schmidt, and A. Smolka
Substantial insured losses occurred during landfall of tropical cyclones (TC) like Hurricane Katrina (2005) in the USA or Typhoon Songda (2004) in Japan, again showing the importance of a sound risk evaluation of TC risk to the insurance industry. This risk evaluation is carried out to assess damage potentials and determine risk-adequate prices using a so-called risk model that consists of three components: hazard, vulnerability, and exposed values.
For hazard evaluation a stochastic simulation of TC tracks is used based on the historical best track data of tropical cyclones in the respective ocean basin (Rumpf et al., 2006 and 2007a). Using this model, synthetic TC tracks covering a time span of 10,000 years are simulated. The model provides the location of the cyclone centre, the maximum wind speed, the radius of maximum wind (RMW) and the radius of gale force winds (Rgale) in six-hour intervals for every simulated TC track according to the information given in the historical data sets. A two-dimensional parametric wind profile based on momentum conservation v = const./(r^x) is applied to the simulated TC tracks, where r represents the radius from the centre of the TC. As momentum is not conserved in the boundary layer, the exponent x < 1 is found empirically from historical storms and depends on the maximum wind speed and the vortex shape parameters RMW and Rgale (Rumpf et al., 2007b).
Vulnerability is evaluated from historical loss and exposure data to obtain a relationship between wind parameters and loss ratio. These parameters include the wind speed and the duration at a certain location, and the size of the storm. Given a certain exposure distribution, the damage of each synthetic storm can be calculated and, assuming the event probability of each synthetic storm is equally distributed, a return period assigned. The resulting probability distribution yields the net premium and damage potentials for specific return periods.
Rumpf J., E. Rauch, V. Schmidt, and H. Weindl, 2006: Stochastic modeling of tropical cyclone track data. 27th Conference on Hurricanes and Tropical Meteorology, April 24 - 28, 2006, Monterey, CA.
Rumpf J., H. Weindl, P. Höppe, E. Rauch, and V. Schmidt, 2007a: Stochastic modelling of tropical cyclone tracks. Math. Meth. Oper. Res., 66, in press.
Rumpf, J., H. Weindl., P. Höppe, and E. Rauch, V. Schmidt, 2007b: Tropical cyclone hazard assessment using model-based track simulation, Natural Hazards, submitted.
Recorded presentationSession 12B, Evaluating Hurricane Risk
Wednesday, 30 April 2008, 3:30 PM-5:15 PM, Palms E
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