A Hidden Semi-Markov Model for Characterizing Regime Shifts in Ocean Density Variability

Summary Societally important decadal predictions of temperature and precipitation over Europe are largely affected by variability in the North Atlantic Ocean. Within this region, the Labrador Sea is of particular importance because of its link between surface-driven density variability and the Atlan...

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Published in:Journal of the Royal Statistical Society Series C: Applied Statistics
Main Authors: Economou, Theodoros, Menary, Matthew B.
Format: Article in Journal/Newspaper
Language:English
Published: Oxford University Press (OUP) 2019
Subjects:
Online Access:http://dx.doi.org/10.1111/rssc.12373
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spelling croxfordunivpr:10.1111/rssc.12373 2023-10-09T21:53:16+02:00 A Hidden Semi-Markov Model for Characterizing Regime Shifts in Ocean Density Variability Economou, Theodoros Menary, Matthew B. 2019 http://dx.doi.org/10.1111/rssc.12373 https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Frssc.12373 https://onlinelibrary.wiley.com/doi/pdf/10.1111/rssc.12373 https://onlinelibrary.wiley.com/doi/full-xml/10.1111/rssc.12373 https://academic.oup.com/jrsssc/article-pdf/68/5/1529/49340987/jrsssc_68_5_1529.pdf en eng Oxford University Press (OUP) https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model Journal of the Royal Statistical Society Series C: Applied Statistics volume 68, issue 5, page 1529-1553 ISSN 0035-9254 1467-9876 Statistics, Probability and Uncertainty Statistics and Probability journal-article 2019 croxfordunivpr https://doi.org/10.1111/rssc.12373 2023-09-22T11:16:25Z Summary Societally important decadal predictions of temperature and precipitation over Europe are largely affected by variability in the North Atlantic Ocean. Within this region, the Labrador Sea is of particular importance because of its link between surface-driven density variability and the Atlantic meridional overturning circulation. Using physical justifications, we propose a statistical model to describe the temporal variability of ocean density in terms of salinity-driven and temperature-driven density. This is a hidden semi-Markov model that allows for either a salinity-driven or a temperature-driven ocean density regime, such that the persistence in each regime is governed probabilistically by a semi-Markov chain. The model is fitted in the Bayesian framework, and a reversible jump Markov chain Monte Carlo algorithm is proposed to deal with a single-regime scenario. The model is first applied to a reanalysis data set, where model checking measures are also proposed. Then it is applied to data from 43 climate models to investigate whether and how ocean density variability differs between them and also the reanalysis data. Parameter estimates relating to the mean holding time for each regime are used to establish a link between regime behaviour and the Atlantic meridional overturning circulation. Article in Journal/Newspaper Labrador Sea North Atlantic Oxford University Press (via Crossref) Journal of the Royal Statistical Society Series C: Applied Statistics 68 5 1529 1553
institution Open Polar
collection Oxford University Press (via Crossref)
op_collection_id croxfordunivpr
language English
topic Statistics, Probability and Uncertainty
Statistics and Probability
spellingShingle Statistics, Probability and Uncertainty
Statistics and Probability
Economou, Theodoros
Menary, Matthew B.
A Hidden Semi-Markov Model for Characterizing Regime Shifts in Ocean Density Variability
topic_facet Statistics, Probability and Uncertainty
Statistics and Probability
description Summary Societally important decadal predictions of temperature and precipitation over Europe are largely affected by variability in the North Atlantic Ocean. Within this region, the Labrador Sea is of particular importance because of its link between surface-driven density variability and the Atlantic meridional overturning circulation. Using physical justifications, we propose a statistical model to describe the temporal variability of ocean density in terms of salinity-driven and temperature-driven density. This is a hidden semi-Markov model that allows for either a salinity-driven or a temperature-driven ocean density regime, such that the persistence in each regime is governed probabilistically by a semi-Markov chain. The model is fitted in the Bayesian framework, and a reversible jump Markov chain Monte Carlo algorithm is proposed to deal with a single-regime scenario. The model is first applied to a reanalysis data set, where model checking measures are also proposed. Then it is applied to data from 43 climate models to investigate whether and how ocean density variability differs between them and also the reanalysis data. Parameter estimates relating to the mean holding time for each regime are used to establish a link between regime behaviour and the Atlantic meridional overturning circulation.
format Article in Journal/Newspaper
author Economou, Theodoros
Menary, Matthew B.
author_facet Economou, Theodoros
Menary, Matthew B.
author_sort Economou, Theodoros
title A Hidden Semi-Markov Model for Characterizing Regime Shifts in Ocean Density Variability
title_short A Hidden Semi-Markov Model for Characterizing Regime Shifts in Ocean Density Variability
title_full A Hidden Semi-Markov Model for Characterizing Regime Shifts in Ocean Density Variability
title_fullStr A Hidden Semi-Markov Model for Characterizing Regime Shifts in Ocean Density Variability
title_full_unstemmed A Hidden Semi-Markov Model for Characterizing Regime Shifts in Ocean Density Variability
title_sort hidden semi-markov model for characterizing regime shifts in ocean density variability
publisher Oxford University Press (OUP)
publishDate 2019
url http://dx.doi.org/10.1111/rssc.12373
https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Frssc.12373
https://onlinelibrary.wiley.com/doi/pdf/10.1111/rssc.12373
https://onlinelibrary.wiley.com/doi/full-xml/10.1111/rssc.12373
https://academic.oup.com/jrsssc/article-pdf/68/5/1529/49340987/jrsssc_68_5_1529.pdf
genre Labrador Sea
North Atlantic
genre_facet Labrador Sea
North Atlantic
op_source Journal of the Royal Statistical Society Series C: Applied Statistics
volume 68, issue 5, page 1529-1553
ISSN 0035-9254 1467-9876
op_rights https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model
op_doi https://doi.org/10.1111/rssc.12373
container_title Journal of the Royal Statistical Society Series C: Applied Statistics
container_volume 68
container_issue 5
container_start_page 1529
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