Title

Uncertainty Analysis For Computer Model Projections Of Hurricane Losses

Keywords

Damage function; Expected percentage reduction; Holland wind field model; Hurricane loss; Latin hypercube sampling; Rank correlation; Saffir-Simpson scale; Sensitivity analysis; Standardized regression coefficients; Uncertainty analysis

Abstract

Projecting losses associated with hurricanes is a complex and difficult undertaking that is wrought with uncertainties. Hurricane Charley, which struck southwest Florida on August 13, 2004, illustrates the uncertainty of forecasting damages from these storms. Due to shifts in the track and the rapid intensification of the storm, real-time estimates grew from $2 to $3 billion in losses late on August 12 to a peak of $50 billion for a brief time as the storm appeared to be headed for the Tampa Bay area. The storm hit the resort areas of Charlotte Harbor near Punta Gorda and then went on to Orlando in the central part of the state, with early poststorm estimates converging on a damage estimate in the $28 to $31 billion range. Comparable damage to central Florida had not been seen since Hurricane Donna in 1960. The Florida Commission on Hurricane Loss Projection Methodology (FCHLPM) has recognized the role of computer models in projecting losses from hurricanes. The FCHLPM established a professional team to perform onsite (confidential) audits of computer models developed by several different companies in the United States that seek to have their models approved for use in insurance rate filings in Florida. The team's members represent the fields of actuarial science, computer science, meteorology, statistics, and wind and structural engineering. An important part of the auditing process requires uncertainty and sensitivity analyses to be performed with the applicant's proprietary model. To influence future such analyses, an uncertainty and sensitivity analysis has been completed for loss projections arising from use of a Holland B parameter hurricane wind field model. Uncertainty analysis quantifies the expected percentage reduction in the uncertainty of wind speed and loss that is attributable to each of the input variables. © 2005 Society for Risk Analysis.

Publication Date

10-1-2005

Publication Title

Risk Analysis

Volume

25

Issue

5

Number of Pages

1299-1312

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1111/j.1539-6924.2005.00674.x

Socpus ID

28144435597 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/28144435597

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