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

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, (Formula presented.) 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

Chaotic variability of the Atlantic meridional overturning circulation at subannual time scales

This study describes the intra- to interannual variability of the Atlantic meridional overturning circulation (AMOC) and the relative dynamical contributions to the total variability in an eddy-resolving 1/128 resolution ocean model. Based on a 53-yr-long hindcast and two 4-yr-long ensembles, we assess the total AMOC variability as well as the variability arising from small differences in the ocean initial state that rapidly imprints on the mesoscale eddy fields and subsequently on large-scale features. This initial-condition-dependent variability will henceforth be referred to as “chaotic” variability. We find that intra-annual AMOC fluctuations are mainly driven by the atmospheric forcing, with the chaotic variability fraction never exceeding 26% of the total variance in the whole meridional Atlantic domain. To understand the nature of the chaotic variability we decompose the AMOC (into its Ekman, geostrophic, barotropic, and residual components). The barotropic and geostrophic AMOC contributions exhibit strong, partly compensating fluctuations, which are linked to chaotic spatial variations of currents over topography. In the North Atlantic, the largest chaotic divergence of ensemble members is found around 248, 388, and 648N. At 26.58N, where the AMOC is monitored by the RAPID– MOCHA array, the chaotic fraction of the AMOC variability is 10%. This fraction is slightly overestimated with the reconstruction methodology as used in the observations (∼15%). This higher fraction of chaotic variability is due to the barotropic contribution not being completely captured by the monitoring system. We look at the strong AMOC decline observed in 2009/10 and find that the ensemble spread (our measure for chaotic variability) was not particularly large during this event

Labrador Sea subsurface density as a precursor of multidecadal variability in the North Atlantic: a multi-model study

The subpolar North Atlantic (SPNA) is a region with prominent decadal variability that has experienced remarkable warming and cooling trends in the last few decades. These observed trends have been preceded by slow-paced increases and decreases in the Labrador Sea density (LSD), which are thought to be a precursor of large-scale ocean circulation changes. This article analyses the interrelationships between the LSD and the wider North Atlantic across an ensemble of coupled climate model simulations. In particular, it analyses the link between subsurface density and the deep boundary density, the Atlantic Meridional Overturning Circulation (AMOC), the subpolar gyre (SPG) circulation, and the upper-ocean temperature in the eastern SPNA. All simulations exhibit considerable multidecadal variability in the LSD and the ocean circulation indices, which are found to be interrelated. LSD is strongly linked to the strength of the subpolar AMOC and gyre circulation, and it is also linked to the subtropical AMOC, although the strength of this relationship is model-dependent and affected by the inclusion of the Ekman component. The connectivity of LSD with the subtropics is found to be sensitive to different model features, including the mean density stratification in the Labrador Sea, the strength and depth of the AMOC, and the depth at which the LSD propagates southward along the western boundary. Several of these quantities can also be computed from observations, and comparison with these observation-based quantities suggests that models representing a weaker link to the subtropical AMOC might be more realistic

Variabilité de la glace de mer en mer du Groenland (liens avec les forçages atmosphériques et océaniques à l'échelle interannuelle)

L'objet de cette thèse est la compréhension des mécanismes contrôlant la variabilité spatio-temporelle de la concentration de glace de mer (SIC) en mer du Groenland, l'un des sites de formation d eau dense de l Atlantique Nord. Cette variabilité est caractérisée à partir des données satellitaires de concentration de glace obtenues par radiométrie hyperfréquence sur la période 1979-2007, en se concentrant sur la période convective (hiver et printemps). Trois modes de variabilité sont identifiés avec une forte dominance du premier mode qui représente 70% de la variance de la SIC dans la région. Les liens statistiques de ces modes avec les forçages atmosphériques sont examinés à partir des réanalyses du centre européen. On montre l'importance de la variabilité du vent méridien sur le mode dominant de SIC par son impact sur la dérive d Ekman et un lien avec la température de surface de l air mettant en jeu la rétroaction de la glace sur l atmosphère via les flux de chaleur. Une étude complémentaire basée sur une classification en régimes de temps de Cassou et al. (2004) montre une réponse préférentielle de la SIC à la phase négative de la NAO. La construction d un jeu de données hydrologiques homogène sur la période 1982-2006 a permis d examiner le lien statistique entre les modes de variabilité de la SIC et l activité convective dans le gyre du Groenland identifiée à partir d un critère de stratification de la colonne d'eau. On met en évidence une corrélation significative entre la variabilité de la convection et le second mode de variabilité de la SIC associant un faible englacement dans le centre du bassin à une forte activité convective.PARIS-BIUSJ-Sci.Terre recherche (751052114) / SudocSudocFranceF

AMOC Predictability estimated through best analog

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Greenland Sea sea ice variability over 1979-2007 and its link to the surface atmosphere

International audienceMean winter Arctic sea ice concentration based on passive microwave observations for the period 1979-2007 are analyzed to examine the variability of the western Nordic Seas marginal ice zone (MIZ). A principal component analysis performed on this regional domain shows that the interannual variability is dominated by a mode which captures more than 70% of the total variance and shows only moderate correlation with the leading mode of global Northern Hemisphere sea ice variability. This mode appears to be related to a pattern of sea level pressure (SLP) anomaly centered on the MIZ with large scale signature resembling the canonical pattern of the North Atlantic Oscillation (NAO). Still this leading mode of SIC variability shows a weak temporal correlation with the NAO index. Taking into account the intrinsic spatial asymmetry found between the two phases of the NAO based on a weather regimes analysis, composite SIC fields are constructed which indeed suggest a preferential response of the Greenland Sea SIC variability to negative NAO-like patterns of SLP. The SLP pattern is consistent with a response of the sea ice margin to the strength of the northerly winds along eastern Greenland. A weak pattern of surface air temperature anomalies also emerges in the central Greenland Sea which occurs, at least partly, as a response of the surface atmosphere to sea ice concentrations changes. Higher order modes of winter SIC variability emerge based on a shorter winter season. One mode has much resemblance with the Odden/Nordbukta pattern while another one exhibits a significant signature in the center of the Greenland Sea convective gyre. The Odden/Nordbukta mode shows a more symmetric relation to the NAO than the leading SIC mode. Linear regression analysis consistently suggests some link between this mode and the ice area flux through Fram Strait

On the robustness of near term climate predictability regarding initial state uncertainties

A set of four ensemble simulations has been designed to assess the relative importance of atmospheric, oceanic, and deep ocean initial state uncertainties, as represented by spatial white noise perturbations, on seasonal to decadal prediction skills in a perfect model framework. It is found that a perturbation mimicking random oceanic uncertainties have the same impact as an atmospheric-only perturbation on the future evolution of the ensemble after the first 3 months, even if they are initially only located in the deep ocean. This is due to the fast (1 month) perturbation of the atmospheric component regardless of the initial ensemble generation strategy. The divergence of the ensemble upper-ocean characteristics is then mainly induced by ocean–atmosphere interactions. While the seasonally varying mixed layer depth allows the penetration of the different signals in the thermocline in the mid-high latitudes, the rapid adjustment of the thermocline to wind anomalies followed by Kelvin and Rossby waves adjustment dominates the growth of the ensemble spread in the tropics. These mechanisms result in similar ensemble distribution characteristics for the four ensembles design strategy at the interannual timescale