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

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  • Darmesah Gabda

    (Universiti Malaysia Sabah)

  • Jonathan Tawn

    (Lancaster University)

  • Simon Brown

    (Met Office Hadley Centre)

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, which 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.

Suggested Citation

  • Darmesah Gabda & Jonathan Tawn & Simon Brown, 2019. "A step towards efficient inference for trends in UK extreme temperatures through distributional linkage between observations and climate model data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 98(3), pages 1135-1154, September.
    • Handle: RePEc:spr:nathaz:v:98:y:2019:i:3:d:10.1007_s11069-018-3504-8
    DOI: 10.1007/s11069-018-3504-8
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    References listed on IDEAS

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    1. V. Chavez‐Demoulin & A. C. Davison, 2005. "Generalized additive modelling of sample extremes," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(1), pages 207-222, January.
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