Systematic Estimates of Decadal Predictability for Six CGCMs

Initial-value predictability measures the degree to which the initial state can influence predictions. In this paper, the initial-value predictability of six atmosphere–ocean general circulation models in the North Pacific and North Atlantic is quantified and contrasted by analyzing long control int...

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Published in:Journal of Climate
Main Authors: Branstator, G., Teng, H., Meehl, G. A., Kimoto, M., Knight, J. R., Latif, Mojib, Rosati, A.
Format: Article in Journal/Newspaper
Language:English
Published: AMS (American Meteorological Society) 2012
Subjects:
Online Access:https://oceanrep.geomar.de/id/eprint/13303/
https://oceanrep.geomar.de/id/eprint/13303/3/JCLI-D-11-00227_publ.pdf
https://doi.org/10.1175/JCLI-D-11-00227.1
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author Branstator, G.
Teng, H.
Meehl, G. A.
Kimoto, M.
Knight, J. R.
Latif, Mojib
Rosati, A.
author_facet Branstator, G.
Teng, H.
Meehl, G. A.
Kimoto, M.
Knight, J. R.
Latif, Mojib
Rosati, A.
author_sort Branstator, G.
collection OceanRep (GEOMAR Helmholtz Centre für Ocean Research Kiel)
container_issue 6
container_start_page 1827
container_title Journal of Climate
container_volume 25
description Initial-value predictability measures the degree to which the initial state can influence predictions. In this paper, the initial-value predictability of six atmosphere–ocean general circulation models in the North Pacific and North Atlantic is quantified and contrasted by analyzing long control integrations with time invariant external conditions. Through the application of analog and multivariate linear regression methodologies, average predictability properties are estimated for forecasts initiated from every state on the control trajectories. For basinwide measures of predictability, the influence of the initial state tends to last for roughly a decade in both basins, but this limit varies widely among the models, especially in the North Atlantic. Within each basin, predictability varies regionally by as much as a factor of 10 for a given model, and the locations of highest predictability are different for each model. Model-to-model variations in predictability are also seen in the behavior of prominent intrinsic basin modes. Predictability is primarily determined by the mean of forecast distributions rather than the spread about the mean. Horizontal propagation plays a large role in the evolution of these signals and is therefore a key factor in differentiating the predictability of the various models.
format Article in Journal/Newspaper
genre North Atlantic
genre_facet North Atlantic
geographic Pacific
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op_doi https://doi.org/10.1175/JCLI-D-11-00227.1
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Branstator, G., Teng, H., Meehl, G. A., Kimoto, M., Knight, J. R., Latif, M. and Rosati, A. (2012) Systematic Estimates of Decadal Predictability for Six CGCMs. Open Access Journal of Climate, 25 (6). pp. 1827-1846. DOI 10.1175/JCLI-D-11-00227.1 <https://doi.org/10.1175/JCLI-D-11-00227.1>.
doi:10.1175/JCLI-D-11-00227.1
op_rights info:eu-repo/semantics/openAccess
publishDate 2012
publisher AMS (American Meteorological Society)
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spelling ftoceanrep:oai:oceanrep.geomar.de:13303 2025-01-16T23:36:07+00:00 Systematic Estimates of Decadal Predictability for Six CGCMs Branstator, G. Teng, H. Meehl, G. A. Kimoto, M. Knight, J. R. Latif, Mojib Rosati, A. 2012 text https://oceanrep.geomar.de/id/eprint/13303/ https://oceanrep.geomar.de/id/eprint/13303/3/JCLI-D-11-00227_publ.pdf https://doi.org/10.1175/JCLI-D-11-00227.1 en eng AMS (American Meteorological Society) https://oceanrep.geomar.de/id/eprint/13303/3/JCLI-D-11-00227_publ.pdf Branstator, G., Teng, H., Meehl, G. A., Kimoto, M., Knight, J. R., Latif, M. and Rosati, A. (2012) Systematic Estimates of Decadal Predictability for Six CGCMs. Open Access Journal of Climate, 25 (6). pp. 1827-1846. DOI 10.1175/JCLI-D-11-00227.1 <https://doi.org/10.1175/JCLI-D-11-00227.1>. doi:10.1175/JCLI-D-11-00227.1 info:eu-repo/semantics/openAccess Article PeerReviewed info:eu-repo/semantics/article 2012 ftoceanrep https://doi.org/10.1175/JCLI-D-11-00227.1 2023-04-07T15:02:10Z Initial-value predictability measures the degree to which the initial state can influence predictions. In this paper, the initial-value predictability of six atmosphere–ocean general circulation models in the North Pacific and North Atlantic is quantified and contrasted by analyzing long control integrations with time invariant external conditions. Through the application of analog and multivariate linear regression methodologies, average predictability properties are estimated for forecasts initiated from every state on the control trajectories. For basinwide measures of predictability, the influence of the initial state tends to last for roughly a decade in both basins, but this limit varies widely among the models, especially in the North Atlantic. Within each basin, predictability varies regionally by as much as a factor of 10 for a given model, and the locations of highest predictability are different for each model. Model-to-model variations in predictability are also seen in the behavior of prominent intrinsic basin modes. Predictability is primarily determined by the mean of forecast distributions rather than the spread about the mean. Horizontal propagation plays a large role in the evolution of these signals and is therefore a key factor in differentiating the predictability of the various models. Article in Journal/Newspaper North Atlantic OceanRep (GEOMAR Helmholtz Centre für Ocean Research Kiel) Pacific Journal of Climate 25 6 1827 1846
spellingShingle Branstator, G.
Teng, H.
Meehl, G. A.
Kimoto, M.
Knight, J. R.
Latif, Mojib
Rosati, A.
Systematic Estimates of Decadal Predictability for Six CGCMs
title Systematic Estimates of Decadal Predictability for Six CGCMs
title_full Systematic Estimates of Decadal Predictability for Six CGCMs
title_fullStr Systematic Estimates of Decadal Predictability for Six CGCMs
title_full_unstemmed Systematic Estimates of Decadal Predictability for Six CGCMs
title_short Systematic Estimates of Decadal Predictability for Six CGCMs
title_sort systematic estimates of decadal predictability for six cgcms
url https://oceanrep.geomar.de/id/eprint/13303/
https://oceanrep.geomar.de/id/eprint/13303/3/JCLI-D-11-00227_publ.pdf
https://doi.org/10.1175/JCLI-D-11-00227.1