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    Rights statement: This is the peer reviewed version of the following article: Winter, H. C. and Tawn, J. A. (2016), Modelling heatwaves in central France: a case-study in extremal dependence. Journal of the Royal Statistical Society: Series C (Applied Statistics), 65: 345–365. doi: 10.1111/rssc.12121 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/rssc.12121/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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Modelling heatwaves in central France: a case-study in extremal dependence

Research output: Contribution to journalJournal article

Published
<mark>Journal publication date</mark>04/2016
<mark>Journal</mark>Journal of the Royal Statistical Society: Series C (Applied Statistics)
Issue number3
Volume65
Number of pages21
Pages (from-to)345-365
<mark>State</mark>Published
Early online date22/09/15
<mark>Original language</mark>English

Abstract

Heatwaves are phenomena that have large social and economic consequences. Understanding and estimating the frequency of such events are of great importance to climate scientists and decision makers. Heatwaves are a type of extreme event which are by definition rare and as such there are few data in the historical record to help planners. Extreme value theory is a general framework from which inference can be drawn from extreme events. When modelling heatwaves it is important to take into account the intensity and duration of events above a critical level as well as the interaction between both factors. Most previous methods assume that the duration distribution is independent of the critical level that is used to define a heatwave: a shortcoming that can lead to incorrect inferences. The paper characterizes a novel method for analysing the temporal dependence of heatwaves with reference to observed temperatures from Orleans in central France. This method enables estimation of the probabilities for heatwave events irrespectively of whether the duration distribution is independent of the critical level. The methods are demonstrated by estimating the probability of an event more severe than the 2003 European heatwave or an event that causes a specified increase in mortality.

Bibliographic note

This is the peer reviewed version of the following article: Winter, H. C. and Tawn, J. A. (2016), Modelling heatwaves in central France: a case-study in extremal dependence. Journal of the Royal Statistical Society: Series C (Applied Statistics), 65: 345–365. doi: 10.1111/rssc.12121 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1111/rssc.12121/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.