The Utility Of Surface Roughness Datasets in the Modeling of United States Hurricane Property Losses
Kimberly Mueller, Risk Management Solutions, Newark, CA; and C. Miller and A. Boissonade
The Utility of Land Use and Topography Data in the Modeling of United States Hurricane Insurance Losses
Kimberly J. Mueller Risk Management Solutions, Newark, CA
Dr. Auguste Boissonade Risk Management Solutions, Newark, CA
Dr. Craig Miller University of Ontario
Catastrophe risk management companies are interested in modeling the wind field of a land falling hurricane at the highest level possible. During a landfalling hurricane, the wind speeds at a particular location change direction and intensity as the hurricane approaches, and are further impacted by surface roughness features upwind as the storm interacts with land, and also by topographic effects. In order to accurately model at the high resolution necessary to assess insurance losses, a high degree of accuracy in modeling terrain and land use features is essential. This paper discusses the pros and cons of using particular datasets and remote sensing techniques in order to obtain a better representation of the surface wind field and a better loss assessment of properties affected by hurricane winds.
High resolution satellite data are used to approach the problem of accurately modeling the effect of surface roughness on very localized wind speeds. Land use/land cover classifications originally were based on NLCD 1992 (National Land Cover Data), and are now updated for urban areas using 15 m ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data of 2002 vintage. Furthermore, the land cover data is stratified into height classes using National Elevation Data in conjuction with STRM (Shuttle Radar Topography Mission) first return topography data, before being assigned to a roughness category. The time-stepping windfield model then considers surface roughness in 8 directions up to 80 km upwind. Topographic features are analyzed, from which speed up effects are assessed using linearized methods.
Extended Abstract (144K)
Session 1, Hazards and disasters: Socioeconomic Impacts & the Decision making process: Part 1
Monday, 30 January 2006, 4:00 PM-5:15 PM, A311
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