Modelling spatial extreme events with environmental applications

Tawn, Jonathan Angus and Shooter, Robert and Towe, Ross Paul and Lamb, Robert (2018) Modelling spatial extreme events with environmental applications. Spatial Statistics, 28. pp. 39-58. ISSN 2211-6753

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Abstract

Spatial extreme value analysis has been an area of rapid growth in the last decade. The focus has been on modelling the spatial componentwise maxima by max-stable processes. Here, we will explain the limitations of these modelling approaches and show how spatial models can be developed that overcome these deficiencies by exploiting the flexible conditional multivariate extremes models of Heffernan and Tawn (2004). We illustrate the benefits of these new spatial models through applications to North Sea wave analysis and to widespread UK river flood risk analysis.

Item Type:

Journal Article

Journal or Publication Title:

Spatial Statistics

Additional Information:

This is the author’s version of a work that was accepted for publication in Spatial Statistics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Spatial Statistics, 28, 2018 DOI: 10.1016/j.spasta.2018.04.007

Uncontrolled Keywords:

/dk/atira/pure/subjectarea/asjc/1900/1903

Subjects:

?? conditional multivariate extreme valuescopulagaussian processesgeneralized pareto distributionmax-stable processespareto processesspatial extremescomputers in earth sciencesstatistics and probabilitymanagement, monitoring, policy and law ??

Departments:

Faculty of Science and Technology > Mathematics and Statistics
Faculty of Science and Technology > School of Computing & Communications

ID Code:

124851

Deposited By:

ep_importer_pure

Deposited On:

25 Apr 2018 09:18

Refereed?:

Yes

Published?:

Published

Last Modified:

21 Feb 2024 00:50

URI:

https://eprints.lancs.ac.uk/id/eprint/124851