Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Estimating Uncertainty in the Extreme Value Analysis of Data Generated by a Hurricane Simulation Model



S Coles, Emil Simiu


Extreme value analyses of any environmental phenomenon are fraught with difficulties, but the additional difficulty of collecting reliable data during hurricane events makes their analysis even more complicated. A widely accepted procedure is to use calibrated hurricane models for the simulation of realistic hurricane events, whose data can be subjected to standard extreme value procedures. The estimation uncertainties which arise from such analyses depend upon (1) the extent to which the hurricane models are physically realistic, (2) the length of the simulated series, which consists of shout 1,000 or even 10,000 simulated events, and therefore introduces negligible errors, and (3) the length of historical record on which the siulated records are based, which usually consists of about 50 events. In this note we propose the use of resampling schemes as an attempting to obtain some reasonable measure of uncertainties due to the relatively short length of the historical record. An intuitive, na ve procedure is first described, which leads to an alternative approach that has connections with the statistical procedure of bootstrapping. Standard application of these procedures for extermes induces bias, and we propose a simple, though non-standrd method for reducing this effect. The results are illustrated on a dataset of simulated hurricane wind speeds for an eastern US coastline location.
Journal of Engineering Mechanics-Asce
No. 11


bootstrap, Building Technology, extremes, hurricane wind speeds, simulation, wind engineering


Coles, S. and Simiu, E. (2003), Estimating Uncertainty in the Extreme Value Analysis of Data Generated by a Hurricane Simulation Model, Journal of Engineering Mechanics-Asce (Accessed July 19, 2024)


If you have any questions about this publication or are having problems accessing it, please contact

Created October 31, 2003, Updated October 12, 2021