A Bayesian spatio-temporal model for precipitation extremes - STOR team contribution to the EVA2017 challenge

Barlow, Anna and Rohrbeck, Christian and Sharkey, Paul and Shooter, Robert and Simpson, Emma (2018) A Bayesian spatio-temporal model for precipitation extremes - STOR team contribution to the EVA2017 challenge. Extremes, 21 (3). pp. 431-439. ISSN 1386-1999

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Abstract

This paper concerns our approach to the EVA2017 challenge, the aim of which was to predict extreme precipitation quantiles across several sites in the Netherlands. Our approach uses a Bayesian hierarchical structure, which combines Gamma and generalised Pareto distributions. We impose a spatio-temporal structure in the model parameters via an autoregressive prior. Estimates are obtained using Markov chain Monte Carlo techniques and spatial interpolation. This approach has been successful in the context of the challenge, providing reasonable improvements over the benchmark.

Item Type: Journal Article
Journal or Publication Title: Extremes
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/s10687-018-0330-z
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/2600/2613
Subjects:
Departments: Faculty of Science and Technology > Mathematics and Statistics
ID Code: 125823
Deposited By: ep_importer_pure
Deposited On: 12 Jun 2018 10:48
Refereed?: Yes
Published?: Published
Last Modified: 22 Feb 2020 04:35
URI: https://eprints.lancs.ac.uk/id/eprint/125823

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