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Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems

Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems
Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems
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,
0930-7575
Sévellec, Florian
01569d6c-65b0-4270-af2a-35b0a77c9140
Dijkstra, Henk A.
9178b06d-9de5-4f02-b9ff-204b20620291
Drijfhout, Sybren S.
a5c76079-179b-490c-93fe-fc0391aacf13
Germe, Agathe
d45e8cfc-49e2-485f-a78c-a295cdae1902
Sévellec, Florian
01569d6c-65b0-4270-af2a-35b0a77c9140
Dijkstra, Henk A.
9178b06d-9de5-4f02-b9ff-204b20620291
Drijfhout, Sybren S.
a5c76079-179b-490c-93fe-fc0391aacf13
Germe, Agathe
d45e8cfc-49e2-485f-a78c-a295cdae1902

Sévellec, Florian, Dijkstra, Henk A., Drijfhout, Sybren S. and Germe, Agathe (2017) Dynamical attribution of oceanic prediction uncertainty in the North Atlantic: application to the design of optimal monitoring systems. Climate Dynamics. (doi:10.1007/s00382-017-3969-2).

Record type: Article

Abstract

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,

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More information

Accepted/In Press date: 11 October 2017
e-pub ahead of print date: 17 November 2017

Identifiers

Local EPrints ID: 416292
URI: http://eprints.soton.ac.uk/id/eprint/416292
ISSN: 0930-7575
PURE UUID: e9ff7659-4e1a-419a-a66a-e389258284c1

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Date deposited: 12 Dec 2017 17:30
Last modified: 06 Oct 2020 16:55

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