State space models for non-stationary intermittently coupled systems: an application to the North Atlantic Oscillation

We develop Bayesian state space methods for modelling changes to the mean level or temporal correlation structure of an observed time series due to intermittent coupling with an unobserved process. Novel intervention methods are proposed to model the effect of repeated coupling as a single dynamic p...

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Bibliographic Details
Main Authors: Sansom, Philip G., Williamson, Daniel B., Stephenson, David B.
Format: Report
Language:unknown
Published: arXiv 2017
Subjects:
Applications stat.AP
FOS Computer and information sciences
North Atlantic
North Atlantic oscillation
Online Access:https://dx.doi.org/10.48550/arxiv.1711.04135
https://arxiv.org/abs/1711.04135
id ftdatacite:10.48550/arxiv.1711.04135
record_format openpolar
spelling ftdatacite:10.48550/arxiv.1711.04135 2023-05-15T17:29:55+02:00 State space models for non-stationary intermittently coupled systems: an application to the North Atlantic Oscillation Sansom, Philip G. Williamson, Daniel B. Stephenson, David B. 2017 https://dx.doi.org/10.48550/arxiv.1711.04135 https://arxiv.org/abs/1711.04135 unknown arXiv arXiv.org perpetual, non-exclusive license http://arxiv.org/licenses/nonexclusive-distrib/1.0/ Applications stat.AP FOS Computer and information sciences Preprint Article article CreativeWork 2017 ftdatacite https://doi.org/10.48550/arxiv.1711.04135 2022-04-01T10:27:42Z We develop Bayesian state space methods for modelling changes to the mean level or temporal correlation structure of an observed time series due to intermittent coupling with an unobserved process. Novel intervention methods are proposed to model the effect of repeated coupling as a single dynamic process. Latent time-varying autoregressive components are developed to model changes in the temporal correlation structure. Efficient filtering and smoothing methods are derived for the resulting class of models. We propose methods for quantifying the component of variance attributable to an unobserved process, the effect during individual coupling events, and the potential for skilful forecasts. The proposed methodology is applied to the study of winter-time variability in the dominant pattern of climate variation in the northern hemisphere, the North Atlantic Oscillation. Around 70% of the inter-annual variance in the winter (Dec-Jan-Feb) mean level is attributable to an unobserved process. Skilful forecasts for winter (Dec-Jan-Feb) mean are possible from the beginning of December. : 27 pages, 8 figures, 4 tables Report North Atlantic North Atlantic oscillation DataCite Metadata Store (German National Library of Science and Technology)
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
topic Applications stat.AP
FOS Computer and information sciences
spellingShingle Applications stat.AP
FOS Computer and information sciences
Sansom, Philip G.
Williamson, Daniel B.
Stephenson, David B.
State space models for non-stationary intermittently coupled systems: an application to the North Atlantic Oscillation
topic_facet Applications stat.AP
FOS Computer and information sciences
description We develop Bayesian state space methods for modelling changes to the mean level or temporal correlation structure of an observed time series due to intermittent coupling with an unobserved process. Novel intervention methods are proposed to model the effect of repeated coupling as a single dynamic process. Latent time-varying autoregressive components are developed to model changes in the temporal correlation structure. Efficient filtering and smoothing methods are derived for the resulting class of models. We propose methods for quantifying the component of variance attributable to an unobserved process, the effect during individual coupling events, and the potential for skilful forecasts. The proposed methodology is applied to the study of winter-time variability in the dominant pattern of climate variation in the northern hemisphere, the North Atlantic Oscillation. Around 70% of the inter-annual variance in the winter (Dec-Jan-Feb) mean level is attributable to an unobserved process. Skilful forecasts for winter (Dec-Jan-Feb) mean are possible from the beginning of December. : 27 pages, 8 figures, 4 tables
format Report
author Sansom, Philip G.
Williamson, Daniel B.
Stephenson, David B.
author_facet Sansom, Philip G.
Williamson, Daniel B.
Stephenson, David B.
author_sort Sansom, Philip G.
title State space models for non-stationary intermittently coupled systems: an application to the North Atlantic Oscillation
title_short State space models for non-stationary intermittently coupled systems: an application to the North Atlantic Oscillation
title_full State space models for non-stationary intermittently coupled systems: an application to the North Atlantic Oscillation
title_fullStr State space models for non-stationary intermittently coupled systems: an application to the North Atlantic Oscillation
title_full_unstemmed State space models for non-stationary intermittently coupled systems: an application to the North Atlantic Oscillation
title_sort state space models for non-stationary intermittently coupled systems: an application to the north atlantic oscillation
publisher arXiv
publishDate 2017
url https://dx.doi.org/10.48550/arxiv.1711.04135
https://arxiv.org/abs/1711.04135
genre North Atlantic
North Atlantic oscillation
genre_facet North Atlantic
North Atlantic oscillation
op_rights arXiv.org perpetual, non-exclusive license
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
op_doi https://doi.org/10.48550/arxiv.1711.04135
_version_ 1766125152064503808

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