Chaotic variability of ocean heat content climate-relevant features and observational implications
Global ocean models that admit mesoscale turbulence spontaneously generate a substantial interannual-to-multidecadal chaotic intrinsic variability in the absence of atmospheric forcing variability at these timescales. This phenomenon is substantially weaker in non-turbulent ocean models but provides...
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ftird:oai:ird.fr:fdi:010074770 2024-09-09T20:07:46+00:00 Chaotic variability of ocean heat content climate-relevant features and observational implications Penduff, T. /Sérazin, Guillaume Leroux, S. Close, S. Molines, J. M. Barnier, B. Bessieres, L. Terray, L. Maze, G. 2018 https://www.documentation.ird.fr/hor/fdi:010074770 EN eng https://www.documentation.ird.fr/hor/fdi:010074770 oai:ird.fr:fdi:010074770 Penduff T., Sérazin Guillaume, Leroux S., Close S., Molines J. M., Barnier B., Bessieres L., Terray L., Maze G. Chaotic variability of ocean heat content climate-relevant features and observational implications. 2018, 31 (2), p. 63-71 text 2018 ftird 2024-08-15T05:57:41Z Global ocean models that admit mesoscale turbulence spontaneously generate a substantial interannual-to-multidecadal chaotic intrinsic variability in the absence of atmospheric forcing variability at these timescales. This phenomenon is substantially weaker in non-turbulent ocean models but provides a marked stochastic flavor to the low-frequency variability in eddying ocean models, which are being coupled to the atmosphere for next-generation climate projections. In order to disentangle the atmospherically forced and intrinsic ocean variabilities, the OCCIPUT (OceaniC Chaos - ImPacts, strUcture, predicTability) project performed a long (1960-2015), large ensemble (50 members) of global ocean/sea ice 1/4 degrees simulations driven by the same atmospheric reanalysis, but with perturbed initial conditions. Subsequent ensemble statistics show that the ocean variability can be seen as a broadband "noise," with characteristic scales reaching multiple decades and basin sizes, locally modulated by the atmospheric variability. In several mid-latitude regions, chaotic processes have more impact than atmospheric variability on both the low-frequency variability and the long-term trends of regional ocean heat content. Consequently, certain climate-relevant oceanic signals cannot be unambiguously attributed to atmospheric variability, raising new issues for the detection, attribution, and interpretation of oceanic heat variability and trends in the presence of mesoscale turbulence. Text Sea ice IRD (Institute de recherche pour le développement): Horizon |
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IRD (Institute de recherche pour le développement): Horizon |
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description |
Global ocean models that admit mesoscale turbulence spontaneously generate a substantial interannual-to-multidecadal chaotic intrinsic variability in the absence of atmospheric forcing variability at these timescales. This phenomenon is substantially weaker in non-turbulent ocean models but provides a marked stochastic flavor to the low-frequency variability in eddying ocean models, which are being coupled to the atmosphere for next-generation climate projections. In order to disentangle the atmospherically forced and intrinsic ocean variabilities, the OCCIPUT (OceaniC Chaos - ImPacts, strUcture, predicTability) project performed a long (1960-2015), large ensemble (50 members) of global ocean/sea ice 1/4 degrees simulations driven by the same atmospheric reanalysis, but with perturbed initial conditions. Subsequent ensemble statistics show that the ocean variability can be seen as a broadband "noise," with characteristic scales reaching multiple decades and basin sizes, locally modulated by the atmospheric variability. In several mid-latitude regions, chaotic processes have more impact than atmospheric variability on both the low-frequency variability and the long-term trends of regional ocean heat content. Consequently, certain climate-relevant oceanic signals cannot be unambiguously attributed to atmospheric variability, raising new issues for the detection, attribution, and interpretation of oceanic heat variability and trends in the presence of mesoscale turbulence. |
format |
Text |
author |
Penduff, T. /Sérazin, Guillaume Leroux, S. Close, S. Molines, J. M. Barnier, B. Bessieres, L. Terray, L. Maze, G. |
spellingShingle |
Penduff, T. /Sérazin, Guillaume Leroux, S. Close, S. Molines, J. M. Barnier, B. Bessieres, L. Terray, L. Maze, G. Chaotic variability of ocean heat content climate-relevant features and observational implications |
author_facet |
Penduff, T. /Sérazin, Guillaume Leroux, S. Close, S. Molines, J. M. Barnier, B. Bessieres, L. Terray, L. Maze, G. |
author_sort |
Penduff, T. |
title |
Chaotic variability of ocean heat content climate-relevant features and observational implications |
title_short |
Chaotic variability of ocean heat content climate-relevant features and observational implications |
title_full |
Chaotic variability of ocean heat content climate-relevant features and observational implications |
title_fullStr |
Chaotic variability of ocean heat content climate-relevant features and observational implications |
title_full_unstemmed |
Chaotic variability of ocean heat content climate-relevant features and observational implications |
title_sort |
chaotic variability of ocean heat content climate-relevant features and observational implications |
publishDate |
2018 |
url |
https://www.documentation.ird.fr/hor/fdi:010074770 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
https://www.documentation.ird.fr/hor/fdi:010074770 oai:ird.fr:fdi:010074770 Penduff T., Sérazin Guillaume, Leroux S., Close S., Molines J. M., Barnier B., Bessieres L., Terray L., Maze G. Chaotic variability of ocean heat content climate-relevant features and observational implications. 2018, 31 (2), p. 63-71 |
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1809941454524514304 |