In order to evaluate potential trends in global natural catastrophe losses, it is important to compensate for changes in asset values and exposures over time. We create a Global Normalized Catastrophe Catalogue covering weatherrelated catastrophe losses in the principal developed (Australia, Canada, Europe, Japan, South Korea, United States) and developing (Caribbean, Central America, China, India, the Philippines) regions of the world. We survey losses from 1950 through 2005, although data availability means that for many regions the record is incomplete for the period before the 1970s even for the largest events. After 1970, when the global record becomes more comprehensive, we find evidence of an annual upward trend for normalized losses of 2% per year. Conclusions are heavily weighted by US losses, and their removal eliminates any statistically significant trend. Large events, such as Hurricane Katrina and China flood losses in the 1990s, also exert a strong impact on trend results. In addition, once national losses are further normalized relative to per capita wealth, the significance of the post-1970 global trend disappears. We find insufficient evidence to claim a statistical relationship between global temperature increase and normalized catastrophe losses.
In this study the impacts of the topography of Bermuda on the damage patterns observed following the passage of Hurricane Fabian over the island on 5 September 2003 are considered. Using a linearized model of atmospheric boundary layer flow over low-slope topography that also incorporates a model for changes of surface roughness, sets of directionally dependent wind speed adjustment factors were calculated for the island of Bermuda. These factors were then used in combination with a time-stepping model for the open water wind field of Hurricane Fabian derived from the Hurricane Research Division Real-Time Hurricane Wind Analysis System (H*Wind) surface wind analyses to calculate the maximum 1-min mean wind speed at locations across the island for the following conditions: open water, roughness changes only, and topography and roughness changes combined. Comparison of the modeled 1-min mean wind speeds and directions with observations from a site on the southeast coast of Bermuda showed good agreement between the two sets of values. Maximum open water wind speeds across the entire island showed very little variation and were of category 2 strength on the Saffir-Simpson scale. While the effects of surface roughness changes on the modeled wind speeds showed very little correlation with the observed damage, the effect of the underlying topography led to maximum modeled wind speeds of category 4 strength being reached in highly localized areas on the island. Furthermore, the observed damage was found to be very well correlated with these regions of topographically enhanced wind speeds, with a very clear trend of increasing damage with increasing wind speeds.
Atlantic hurricane activity has been particularly high since 1995, with nine seasons recording more hurricanes than the long‐term average. The recognition that current activity is not the same as the long‐term historical average means that, for the purpose of catastrophe risk assessment, we need to be explicit as to the time period over which expected activity is evaluated. We have chosen to explore activities over a 5‐yr forward looking time window, which bounds the range of business applications for which catastrophe loss models are employed. This time horizon is also shorter than the pattern of past multidecadal periods of high and low activity. The methodology used to assess activity rates for the next 5 yr contains a blend of statistical analyses and an expert elicitation. A panel of experts was convened to discuss expected levels of activity for the next 5 yr across the Atlantic, along the U.S. and Caribbean coasts. The results indicate hurricane activities along the U.S. coast are expected to be between 20 and 35% higher than the long‐term average, depending on storm intensity. The implementation of these findings has included work to determine how increases are distributed by track type and by region, and the impacts on expected losses.
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