Millennial Variability in an Idealized Ocean Model: Predicting the AMOC Regime Shifts

A salient feature of paleorecords of the last glacial interval in the North Atlantic is pronounced millennial variability, commonly known as Dansgaard–Oeschger events. It is believed that these events are related to variations in the Atlantic meridional overturning circulation and heat transport. Here, the authors formulate a new low-order model, based on the Howard–Malkus loop representation of ocean circulation, capable of reproducing millennial variability and its chaotic dynamics realistically. It is shown that even in this chaotic model changes in the state of the meridional overturning circulation are predictable. Accordingly, the authors define two predictive indices which give accurate predictions for the time the circulation should remain in the on phase and then stay in the subsequent off phase. These indices depend mainly on ocean stratification and describe the linear growth of small perturbations in the system. Thus, monitoring particular indices of the ocean state could help predict a potential shutdown of the overturning circulation

Multidecadal variability of the overturning circulation in presence of eddy turbulence

At low-resolution, idealized ocean circulation models forced by prescribed differential surface heat fluxes show spontaneous multidecadal variability depending critically on eddy diffusivity coefficients. The existence of this critical threshold in the range of observational estimates legitimates some doubt on the relevance of such intrinsic oscillations in the real ocean. Through a series of numerical simulations with increasing resolution up to eddy-resolving ones (10 km) and various diapycnal diffusivities, this multidecadal variability proves a generic ubiquitous feature, at least in model versions with a flat bottom. The mean circulation largely changes in the process of refining the horizontal grid (along with the associated implicit viscosity and diffusivity), and the spatial structure of the variability is largely modified, but there is no clear influence of the resolution on the main oscillation period. The interdecadal variability appears even more robust to low vertical diffusivity and overturning when mesoscale eddies are resolved. The mechanism previously proposed for these oscillations, involving westward-propagating baroclinically unstable Rossby waves in the subpolar region and its feedback on the mean circulation, appears unaffected by mesoscale turbulence and is simply displaced following the polar front

Tracking water masses using passive-tracer transport in NEMO v3.4 with NEMOTAM: application to North Atlantic Deep Water and North Atlantic Subtropical Mode Water

Water mass ventilation provides an important link between the atmosphere and the global ocean circulation. In this study, we present a newly developed, probabilistic tool for offline water mass tracking. In particular, NEMOTAM, the tangent-linear and adjoint counterpart to the NEMO ocean general circulation model, is modified to allow passive-tracer transport. By terminating dynamic feedbacks in NEMOTAM, tagged water can be tracked forward and backward in time as a passive dye, producing a probability distribution of pathways and origins, respectively. To represent surface (re-)ventilation, we optionally decrease the tracer concentration in the surface layer and track this concentration removal to produce a ventilation record. Two test cases are detailed, examining the creation and fate of North Atlantic Subtropical Mode Water (NASMW) and North Atlantic Deep Water (NADW) in a 2∘ configuration of NEMO run with repeated annual forcing for up to 400 years. Model NASMW is shown to have an expected age of 4.5 years and is predominantly eradicated by internal processes. A bed of more persistent NASMW is detected below the mixed layer with an expected age of 8.7 years. It is shown that while model NADW has two distinct outcrops (in the Arctic and North Atlantic), its formation primarily takes place in the subpolar Labrador and Irminger seas. Its expected age is 112 years

Surging of global surface temperature due to decadal legacy of ocean heat uptake

Global surface warming since 1850 consisted of a series of slowdowns (hiatus) followed by surges. Knowledge of a mechanism to explain how this occurs would aid development and testing of interannual to decadal climate forecasts. In this paper a global climate model is forced to adopt an ocean state corresponding to a hiatus (with negative Interdecadal Pacific Oscillation, IPO, and other surface features typical of a hiatus) by artificially increasing the background diffusivity for a decade before restoring it to its normal value and allowing the model to evolve freely. This causes the model to develop a decadal surge which overshoots equilibrium (resulting in a positive IPO state) leaving behind a modified, warmer climate for decades. Water mass transformation diagnostics indicate that the heat budget of the tropical Pacific is a balance between large opposite signed terms: surface heating/cooling due to air-sea heat flux is balanced by vertical mixing and ocean heat transport divergence. During the artificial hiatus, excess heat becomes trapped just above the thermocline and there is a weak vertical thermal gradient (due to the high artificial background mixing). When the hiatus is terminated, by returning the background diffusivity to normal, the thermal gradient strengthens to pre-hiatus values so that the mixing (diffusivity x thermal gradient) remains roughly constant. However, since the base layer just above the thermocline remains anomalously warm this implies a warming of the entire water column above the trapped heat which results in a surge followed by a prolonged period of elevated surface temperatures

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

Optimal surface salinity perturbations of the meridional overturning and heat transport in a global ocean general circulation model

Recent observations and modeling studies have stressed the influence of surface salinity perturbations on the North Atlantic circulation over the past few decades. As a step toward the estimation of the sensitivity of the thermohaline circulation to salinity anomalies, optimal initial surface salinity perturbations are computed and described for a realistic mean state of a global ocean general circulation model [Océan Parallélisé (OPA)]; optimality is defined successively with respect to the meridional overturning circulation intensity and the meridional heat transport maximum. Although the system is asymptotically stable, the nonnormality of the dynamics is able to produce a transient growth through an initial stimulation. Optimal perturbations are calculated subject to three constraints: the perturbation applies to surface salinity; the perturbation conserves the global salt content; and the perturbation is normalized, to remove the degeneracy in the linear maximization problem. Maximization using Lagrangian multipliers leads to explicit solutions (rather than eigenvalue problems), involving the integration of the model adjoint for each value to maximize.The most efficient transient growth for the intensity of the meridional overturning circulation appears for a delay of 10.5 yr after the perturbation by the optimal surface salinity anomaly. This optimal growth is induced by an initial anomaly located north of 50°N. In the same way, the most efficient transient growth for the intensity of the meridional heat transport appears for a shorter delay of 2.2 yr after the perturbation by the optimal surface salinity anomaly. This initial optimal perturbation corresponds to a zonal salinity gradient around 24°N. The optimal surface salinity perturbations studied herein yield upper bounds on the intensity of the response in meridional overturning circulation and meridional heat transport. Using typical amplitudes of the Great Salinity Anomalies, the upper bounds for the associated variability are 0.8 Sv (1 Sv ? 106 m3 s?1) (11% of the mean circulation) and 0.03 PW (5% of the mean circulation), respectively

Spatio-temporal evolution of global surface temperature distributions

Climate is known for being characterised by strong non-linearity and chaotic behaviour. Nevertheless, few studies in climate science adopt statistical methods specifically designed for non-stationary or non-linear systems. Here we show how the use of statistical methods from Information Theory can describe the non-stationary behaviour of climate fields, unveiling spatial and temporal patterns that may otherwise be difficult to recognize. We study the maximum temperature at two meters above ground using the NCEP CDAS1 daily reanalysis data, with a spatial resolution of 2.5 by 2.5 degree and covering the time period from 1 January 1948 to 30 November 2018. The spatial and temporal evolution of the temperature time series are retrieved using the Fisher Information Measure, which quantifies the information in a signal, and the Shannon Entropy Power, which is a measure of its uncertainty -- or unpredictability. The results describe the temporal behaviour of the analysed variable. Our findings suggest that tropical and temperate zones are now characterized by higher levels of entropy. Finally, Fisher-Shannon Complexity is introduced and applied to study the evolution of the daily maximum surface temperature distributions.Comment: 7 pages, 4 figure