Work

Detection of changes in the characteristics of oceanographic time-series using changepoint analysis.

Year: 2010

Type: article

Abstract: Changepoint analysis is used to detect changes in variability within GOMOS hindcast time-series for significant wave heights of storm peak events across the Gulf of Mexico for the period 1900–2005. To detect a change in variance, the two-step procedure consists of (1) validating model assumptions per geographic location, followed by (2) application of a penalized likelihood changepoint algorithm. Results suggest that the most important changes in time-series variance occur in 1916 and 1933 at small clusters of boundary locations at which, in general, the variance reduces. No post-war changepoints are detected. The changepoint procedure can be readily applied to other environmental time-series.

Source: Lancaster EPrints (Lancaster University)

Authors: Rebecca Killick, Idris A. Eckley, Philip Jonathan, Kevin Ewans

Language: English

Topic: Advanced Statistical Process Monitoring

Subfield: Statistics, Probability and Uncertainty

Field: Decision Sciences

Domain: Social Sciences

SDG: Climate action

Open Access status: green

Funder: Engineering and Physical Sciences Research Council

OpenAlex ID: W134591693

FWCI: 1.332

Cites: 23

Cited by: 9

Related to: 10