A step towards efficient inference for trends in UK extreme temperatures through distributional linkage between observations and climate model data

Tawn, Jonathan Angus and Gabda, Darmesah and Brown, Simon (2019) A step towards efficient inference for trends in UK extreme temperatures through distributional linkage between observations and climate model data. Natural Hazards, 98 (3). 1135–1154. ISSN 0921-030X

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Abstract

The aim of this paper is to set out a strategy for improving the inference for statistical models for the distribution of annual maxima observed temperature data, with a particular focus on past and future trend estimation. The observed data are on a 25 km grid over the UK. The method involves developing a distributional linkage with models for annual maxima temperatures from an ensemble of regional and global climate numerical models. This formulation enables additional information to be incorporated through the longer records, stronger climate change signals, replications over the ensemble and spatial pooling of information over sites. We find evidence for a common trend between the observed data and the average trend over the ensemble with very limited spatial variation in the trends over the UK. The proposed model, that accounts for all the sources of uncertainty, requires a very high dimensional parametric fit, so we develop an operational strategy based on simplifying assumptions and discuss what is required to remove these restrictions. With such simplifications we demonstrate more than an order of magnitude reduction in the local response of extreme temperatures to global mean temperature changes.

Item Type:
Journal Article
Journal or Publication Title:
Natural Hazards
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1900
Subjects:
?? climatological datadistributional linkagegeneralised extreme value distributionspatial extremestemperature dataearth and planetary sciences(all)mathematics(all)earth and planetary sciences (miscellaneous)water science and technologyatmospheric sciencedisc ??
ID Code:
128164
Deposited By:
Deposited On:
15 Oct 2018 16:03
Refereed?:
Yes
Published?:
Published
Last Modified:
11 Jan 2024 00:20