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...
Published in: | Journal of the Royal Statistical Society Series C: Applied Statistics |
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Online Access: | 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 |
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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 |
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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 |
op_container_end_page |
1553 |
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1779316528497295360 |