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Article overview
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Bayesian spatial extreme value analysis of maximum temperatures in County Dublin, Ireland | | John O'Sullivan
; Conor Sweeney
; Andrew C. Parnell
; | | Date: |
16 Jun 2019 | | Abstract: | In this study, we begin a comprehensive characterisation of temperature
extremes in Ireland for the period 1981-2010. We produce return levels of
anomalies of daily maximum temperature extremes for an area over Ireland, for
the 30-year period 1981-2010. We employ extreme value theory (EVT) to model the
data using the generalised Pareto distribution (GPD) as part of a three-level
Bayesian hierarchical model. We use predictive processes in order to solve the
computationally difficult problem of modelling data over a very dense spatial
field. To our knowledge, this is the first study to combine predictive
processes and EVT in this manner. The model is fit using Markov chain Monte
Carlo (MCMC) algorithms. Posterior parameter estimates and return level
surfaces are produced, in addition to specific site analysis at synoptic
stations, including Casement Aerodrome and Dublin Airport. Observational data
from the period 2011-2018 is included in this site analysis to determine if
there is evidence of a change in the observed extremes. An increase in the
frequency of extreme anomalies, but not the severity, is observed for this
period. We found that the frequency of observed extreme anomalies from
2011-2018 at the Casement Aerodrome and Phoenix Park synoptic stations exceed
the upper bounds of the credible intervals from the model by 20% and 7%
respectively. | | Source: | arXiv, 1906.6744 | | Services: | Forum | Review | PDF | Favorites | |
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