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11 - Integrating hurricane loss models with climate models

Published online by Cambridge University Press:  14 September 2009

Charles C. Watson Jr.
Affiliation:
Kinetic Analysis Corporation, 330, Columbus Drive, Savannah, GA 31405, USA
Mark E. Johnson
Affiliation:
Department of Statistics and Actuarial Science, University of Central Florida, Orlando, FL 32816-2370, USA
Henry F. Diaz
Affiliation:
National Oceanic and Atmospheric Administration, District of Columbia
Richard J. Murnane
Affiliation:
Bermuda Biological Station for Research, Garrett Park, Maryland
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Summary

Condensed summary

Hurricane loss modeling has become an important if not vital aspect of many elements of hurricane planning, especially in the financial sector. The insurance industry has provided financial motivation for the development of complex hurricane damage and loss models. These models rely on a number of databases and model subcomponents that interact in complex ways, the most critical of which is hurricane climatology. The required hurricane climatology is developed through various analyses of the historical record. Unfortunately, there are numerous issues with the historical record that make detailed analysis of that record problematic, such as the length of the record, the quality of the observations, and the potential that the record is complicated by natural or anthropogenic climate signals. As climate modeling continues to advance, there is increasing potential for the use of these models to drive loss models, overcoming many of the limitations of the existing historical record. Here we describe the results of a study conducted for the Florida Commission on Hurricane Loss Projection Methodology (FCHLPM), a part of which was an assessment of historical hurricane climatology, and the potential for the use of general circulation climate models in driving loss models for both existing and future climates. The Community Climate System Model (CCSM) was used to drive a mesoscale model, which in turn was used to create inputs to an ensemble of loss models.

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Publisher: Cambridge University Press
Print publication year: 2008

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