Title
Fitting Statistical Distributions To Data In Hurricane Modeling
Keywords
Data quality; Extreme events; Probabilistic risk analysis; Return period; Weibull distribution
Abstract
Fitting probability distributions to hurricane related data is an essential activity in hurricane planning, designing structures, and catastrophe modeling applications. The recent devastating hurricane seasons and the resultant debates over design criteria and computer models using analyses based on these fits motivate a closer examination of this issue. The primary objective in this paper is to describe the background and applications of historical hurricane data fitting, the operational aspects of which have dictated adjustments to the standard methodology. The emphasis here is on the interaction between data quality and dynamics, the need for rapid but stable assessments of that data, and statistical fitting methodologies. Validation and applications are discussed, along with an analysis of the return periods of damage in the New Orleans area. © 2007, Taylor & Francis Group, LLC. All rights reserved.
Publication Date
1-1-2007
Publication Title
American Journal of Mathematical and Management Sciences
Volume
27
Issue
3-4
Number of Pages
479-498
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1080/01966324.2007.10737710
Copyright Status
Unknown
Socpus ID
43949103112 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/43949103112
STARS Citation
Johnson, Mark E. and Watson, Charles C., "Fitting Statistical Distributions To Data In Hurricane Modeling" (2007). Scopus Export 2000s. 7036.
https://stars.library.ucf.edu/scopus2000/7036