Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems
International audience In this study, the relation between two approaches to assess the ocean predictability on interannual to decadal time scales is investigated. The first pragmatic approach consists of sampling the initial condition uncertainty and assess the predictability through the divergence...
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ftccsdartic:oai:HAL:hal-02136537v1 2023-12-03T10:26:32+01:00 Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems Sévellec, Florian Dijkstra, Henk, Anton Drijfhout, Sybren Germe, Agathe Ocean and Earth Science Southampton University of Southampton-National Oceanography Centre (NOC) Institute for Marine and Atmospheric Research Utrecht (IMAU) Universiteit Utrecht / Utrecht University Utrecht Royal Netherlands Meteorological Institute (KNMI) 2018-08 https://hal.science/hal-02136537 https://hal.science/hal-02136537/document https://hal.science/hal-02136537/file/sevellec_et_al-CD18.pdf https://doi.org/10.1007/s00382-017-3969-2 en eng HAL CCSD Springer Verlag info:eu-repo/semantics/altIdentifier/doi/10.1007/s00382-017-3969-2 hal-02136537 https://hal.science/hal-02136537 https://hal.science/hal-02136537/document https://hal.science/hal-02136537/file/sevellec_et_al-CD18.pdf doi:10.1007/s00382-017-3969-2 info:eu-repo/semantics/OpenAccess ISSN: 0930-7575 EISSN: 1432-0894 Climate Dynamics https://hal.science/hal-02136537 Climate Dynamics, 2018, 51 (4), pp.1517-1535. ⟨10.1007/s00382-017-3969-2⟩ [SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere info:eu-repo/semantics/article Journal articles 2018 ftccsdartic https://doi.org/10.1007/s00382-017-3969-2 2023-11-05T00:05:15Z International audience In this study, the relation between two approaches to assess the ocean predictability on interannual to decadal time scales is investigated. The first pragmatic approach consists of sampling the initial condition uncertainty and assess the predictability through the divergence of this ensemble in time. The second approach is provided by a theoretical framework to determine error growth by estimating optimal linear growing modes. In this paper, it is shown that under the assumption of linearized dynamics and normal distributions of the uncertainty, the exact quantitative spread of ensemble can be determined from the theoretical framework. This spread is at least an order of magnitude less expensive to compute than the approximate solution given by the pragmatic approach. This result is applied to a state-of-the-art Ocean General Circulation Model to assess the predictability in the North Atlantic of four typical oceanic metrics: the strength of the Atlantic Meridional Overturning Circulation (AMOC), the intensity of its heat transport, the two-dimensional spatially-averaged Sea Surface Temperature (SST) over the North Atlantic, and the three-dimensional spatially-averaged temperature in the North Atlantic. For all tested metrics, except for SST, ∼ 75% of the total uncertainty on interannual time scales can be attributed to oceanic initial condition uncertainty rather than atmospheric stochastic forcing. The theoretical method also provide the sensitivity pattern to the initial condition uncertainty, allowing for targeted measurements to improve the skill of the prediction. It is suggested that a relatively small fleet of several autonomous underwater vehicles can reduce the uncertainty in AMOC strength prediction by 70% for 1-5 years lead times. Article in Journal/Newspaper North Atlantic Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) Climate Dynamics 51 4 1517 1535 |
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Open Polar |
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Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe) |
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ftccsdartic |
language |
English |
topic |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
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[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere Sévellec, Florian Dijkstra, Henk, Anton Drijfhout, Sybren Germe, Agathe Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems |
topic_facet |
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean Atmosphere |
description |
International audience In this study, the relation between two approaches to assess the ocean predictability on interannual to decadal time scales is investigated. The first pragmatic approach consists of sampling the initial condition uncertainty and assess the predictability through the divergence of this ensemble in time. The second approach is provided by a theoretical framework to determine error growth by estimating optimal linear growing modes. In this paper, it is shown that under the assumption of linearized dynamics and normal distributions of the uncertainty, the exact quantitative spread of ensemble can be determined from the theoretical framework. This spread is at least an order of magnitude less expensive to compute than the approximate solution given by the pragmatic approach. This result is applied to a state-of-the-art Ocean General Circulation Model to assess the predictability in the North Atlantic of four typical oceanic metrics: the strength of the Atlantic Meridional Overturning Circulation (AMOC), the intensity of its heat transport, the two-dimensional spatially-averaged Sea Surface Temperature (SST) over the North Atlantic, and the three-dimensional spatially-averaged temperature in the North Atlantic. For all tested metrics, except for SST, ∼ 75% of the total uncertainty on interannual time scales can be attributed to oceanic initial condition uncertainty rather than atmospheric stochastic forcing. The theoretical method also provide the sensitivity pattern to the initial condition uncertainty, allowing for targeted measurements to improve the skill of the prediction. It is suggested that a relatively small fleet of several autonomous underwater vehicles can reduce the uncertainty in AMOC strength prediction by 70% for 1-5 years lead times. |
author2 |
Ocean and Earth Science Southampton University of Southampton-National Oceanography Centre (NOC) Institute for Marine and Atmospheric Research Utrecht (IMAU) Universiteit Utrecht / Utrecht University Utrecht Royal Netherlands Meteorological Institute (KNMI) |
format |
Article in Journal/Newspaper |
author |
Sévellec, Florian Dijkstra, Henk, Anton Drijfhout, Sybren Germe, Agathe |
author_facet |
Sévellec, Florian Dijkstra, Henk, Anton Drijfhout, Sybren Germe, Agathe |
author_sort |
Sévellec, Florian |
title |
Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems |
title_short |
Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems |
title_full |
Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems |
title_fullStr |
Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems |
title_full_unstemmed |
Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems |
title_sort |
dynamical attribution of oceanic prediction uncertainty in the north atlantic: application to the design of optimal monitoring systems |
publisher |
HAL CCSD |
publishDate |
2018 |
url |
https://hal.science/hal-02136537 https://hal.science/hal-02136537/document https://hal.science/hal-02136537/file/sevellec_et_al-CD18.pdf https://doi.org/10.1007/s00382-017-3969-2 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_source |
ISSN: 0930-7575 EISSN: 1432-0894 Climate Dynamics https://hal.science/hal-02136537 Climate Dynamics, 2018, 51 (4), pp.1517-1535. ⟨10.1007/s00382-017-3969-2⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1007/s00382-017-3969-2 hal-02136537 https://hal.science/hal-02136537 https://hal.science/hal-02136537/document https://hal.science/hal-02136537/file/sevellec_et_al-CD18.pdf doi:10.1007/s00382-017-3969-2 |
op_rights |
info:eu-repo/semantics/OpenAccess |
op_doi |
https://doi.org/10.1007/s00382-017-3969-2 |
container_title |
Climate Dynamics |
container_volume |
51 |
container_issue |
4 |
container_start_page |
1517 |
op_container_end_page |
1535 |
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1784275862772776960 |