This study uses an existing catalog of registered tornadoes over the territory of the United States to construct a numerical model for tornado loss assessment. The model is tested for the state of Oklahoma (OK). The aggregated annual (AGG) tornado losses are modelled as a function of (1) annual frequency of tornadoes, (2) intensity, length and width of tornado tracks, (3) exposure and (4) vulnerability derived using literature information. Three different configurations of input parameters are investigated: (NoVar) all input parameters except for the annual number of tornadoes are derived based on their mean values, (HOV) variability of house prices, track orientation and vulnerability values are included, and (HOVI) variability of tornado intensity along track length and width is introduced. The calculated AGG losses from independent model runs show high level of convergence for 1000 years of simulated tornadoes. The largest differences in the exceedance probability loss curves result from introducing variability in intensity along the tornado tracks (HOVI). We ran proxies for calculating Risk-Based Capital in order to understand the impact of these findings for policy makers and/or the insurance industry. Modelled losses are compared against results from a commercial tornado risk assessment model as well as against the 2013 Moore tornado event. The NoVar and HOV cases predict the 2013 Moore twister to be 1 in 10 and 1 in 12.5 loss event, respectively, whereas the HOVI case estimates the return period of this event at 58 years. Probability of being hit by a tornado in OK is calculated to be 0.039%, which is in accordance with literature. The limitations and uncertainties of developed model are also discussed.
關聯:
International Journal of Disaster Risk Reduction 16, P.19-32
