A Technique to Measure Trends in the Frequency of Discrete Random Events

Time series of extreme meteorological and hydrological events frequently present problems with the use of traditional parametric statistical techniques. These difficulties arise from the frequent use of count data, the presence of zero values, data with nonnormal distributions, and/or truncated data...

Full description

Saved in:
Bibliographic Details
Published in:Journal of climate 1998-05, Vol.11 (5), p.848-855
Main Authors: Keim, Barry D., Cruise, James F.
Format: Article
Language:English
Subjects:
Cruises
Datasets
Earth, ocean, space
Exact sciences and technology
External geophysics
Floods
Geophysics. Techniques, methods, instrumentation and models
Linear regression
Poisson process
Rain
Statistical variance
Storms
Time series
Weather
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Time series of extreme meteorological and hydrological events frequently present problems with the use of traditional parametric statistical techniques. These difficulties arise from the frequent use of count data, the presence of zero values, data with nonnormal distributions, and/or truncated data. This paper presents a parametric method to evaluate temporal trends in extreme events that overcomes these problems. The technique includes the testing of the arrival structure of extreme event data for the Poisson distribution, then prepares and tests time series of interarrival times for trend analysis through linear regression. Nor’easters along the east coast of the United States and heavy rainfall events at Covington, Louisiana, are examined.
ISSN:0894-8755
1520-0442
DOI:10.1175/1520-0442(1998)011<0848:ATTMTI>2.0.CO;2