Laure Zanna

The signature of low frequency oceanic forcing in the Atlantic Multidecadal Oscillation

The Atlantic Multidecadal Oscillation (AMO) significantly influences the climate of the surrounding continents and has previously been attributed to variations in the Atlantic Meridional Overturning Circulation. Recently, however, similar multidecadal variability was reported in climate models without ocean circulation variability. We analyse the relationship between turbulent heat fluxes and SSTs over the midlatitude North Atlantic in observations and coupled climate model simulations, both with and without ocean circulation variability. SST anomalies associated with the AMO are positively correlated with heat fluxes on decadal time-scales in both observations and models with varying ocean circulation, whereas in models without ocean circulation variability the anomalies are negatively correlated when heat flux anomalies lead. These relationships are captured in a simple stochastic model and rely crucially on low frequency forcing of SST. The fully coupled models that better capture this signature more effectively reproduce the observed impact of the AMO on European summertime temperatures.

Nonnormal Thermohaline Circulation Dynamics in a Coupled Ocean–Atmosphere GCM

Abstract Using the GFDL coupled atmosphere–ocean general circulation model CM2.1, the transient amplification of thermohaline circulation (THC) anomalies due to its nonnormal dynamics is studied. A reduced space based on empirical orthogonal functions (EOFs) of temperature and salinity anomaly fields in the North Atlantic is constructed. Under the assumption that the dynamics of this reduced space is linear, the propagator of the system is then evaluated and the transient growth of THC anomalies analyzed. Although the linear dynamics are stable, such that any initial perturbation eventually decays, nonnormal effects are found to result in a significant transient growth of temperature, salinity, and THC anomalies. The growth time scale for these anomalies is between 5 and 10 yr, providing an estimate of the predictability time of the North Atlantic THC in this model. There are indications that these results are merely a lower bound on the nonnormality of THC dynamics in the present coupled GCM. This seems ...

Nonnormal Amplification of the Thermohaline Circulation

A simple zonally averaged coupled ocean–atmosphere model, with a relatively high resolution in the meridional direction, is used to examine physical mechanisms leading to transient amplification of thermohaline circulation (THC) anomalies. It is found that in a stable regime, in which small perturbations eventually decay, there are optimal initial conditions leading to a dramatic amplification of initial temperature and salinity anomalies in addition to the THC amplification. The maximum amplification occurs after about 40 years, and the eventual decay is on a centennial time scale. The initial temperature and salinity anomalies are considerably amplified by factors of a few hundreds and 20, respectively. The initial conditions leading to this amplification are characterized by mutually canceling initial temperature and salinity anomalies contributions to the THC anomaly, such that the initial THC anomaly vanishes. The mechanism of amplification is analyzed and found to be the result of an interaction between a few damped (oscillatory and nonoscillatory) modes with decay time scales lying in a range of 20–800 years. The amplification mechanism is also found to be distinct from the advective feedback leading to THC instabilities for large freshwater forcing.

Optimal Excitation of Interannual Atlantic Meridional Overturning Circulation Variability

The optimal excitation of Atlantic meridional overturning circulation (MOC) anomalies is investigated in an ocean general circulation model with an idealized configuration. The optimal three-dimensional spatial structure of temperature and salinity perturbations, defined as the leading singular vector and generating the maximum amplification of MOC anomalies, is evaluated by solving a generalized eigenvalue problem using tangent linear and adjoint models. Despite the stable linearized dynamics, a large amplification of MOC anomalies, mostly due to the interference of nonnormal modes, is initiated by the optimal perturbations. The largest amplification of MOC anomalies, found to be excited by high-latitude deep density perturbations in the northern part of the basin, is achieved after about 7.5 years. The anomalies grow as a result of a conversion of mean available potential energy into potential and kinetic energy of the perturbations, reminiscent of baroclinic instability. The time scale of growth of MOC anomalies can be understood by examining the time evolution of deep zonal density gradients, which are related to the MOC via the thermal wind relation. The velocity of propagation of the density anomalies, found to depend on the horizontal component of the mean flow velocity and the mean density gradient, determines the growth time scale of the MOC anomalies and therefore provides an upper bound on the MOC predictability time. The results suggest that the nonnormal linearized ocean dynamics can give rise to enhanced MOC variability if, for instance, overflows, eddies, and/or deep convection can excite high-latitude density anomalies in the ocean interior with a structure resembling that of the optimal perturbations found in this study. The findings also indicate that errors in ocean initial conditions or in model parameterizations or processes, particularly at depth, may significantly reduce the Atlantic MOC predictability time to less than a decade.

Forecast Skill and Predictability of Observed Atlantic Sea Surface Temperatures

AbstractAn empirical statistical model is constructed to assess the forecast skill and the linear predictability of Atlantic Ocean sea surface temperature (SST) variability. Linear inverse modeling (LIM) is used to build a dynamically based statistical model using observed Atlantic SST anomalies between latitudes 20°S and 66°N from 1870 to 2009. LIM allows one to fit a multivariate red-noise model to the observed annually averaged SST anomalies and to test it. Forecast skill is assessed and is shown to be O(3–5 yr). After a few years, the skill is greatly reduced, especially in the subpolar region. In the stable dynamical system determined by LIM, skill of annual average SST anomalies arises from four damped eigenmodes. The four eigenmodes are shown to be relevant in particular for the optimal growth events of SST variance, with a pattern reminiscent of the low-frequency mode of variability, and in general for the predictability and variability of Atlantic SSTs on interannual time scales. LIM might serve ...

A conceptual model of ocean heat uptake under climate change

AbstractA conceptual model of ocean heat uptake is developed as a multilayer generalization of Gnanadesikan. The roles of Southern Ocean Ekman and eddy transports, North Atlantic Deep Water (NADW) formation, and diapycnal mixing in controlling ocean stratification and transient heat uptake are investigated under climate change scenarios, including imposed surface warming, increased Southern Ocean wind forcing, with or without eddy compensation, and weakened meridional overturning circulation (MOC) induced by reduced NADW formation. With realistic profiles of diapycnal mixing, ocean heat uptake is dominated by Southern Ocean Ekman transport and its long-term adjustment controlled by the Southern Ocean eddy transport. The time scale of adjustment setting the rate of ocean heat uptake increases with depth. For scenarios with increased Southern Ocean wind forcing or weakened MOC, deepened stratification results in enhanced ocean heat uptake. In each of these experiments, the role of diapycnal mixing in settin...

Singular vectors, predictability and ensemble forecasting for weather and climate

The local instabilities of a nonlinear dynamical system can be characterized by the leading singular vectors of its linearized operator. The leading singular vectors are perturbations with the greatest linear growth and are therefore key in assessing the system’s predictability. In this paper, the analysis of singular vectors for the predictability of weather and climate and ensemble forecasting is discussed. An overview of the role of singular vectors in informing about the error growth rate in numerical models of the atmosphere is given. This is followed by their use in the initialization of ensemble weather forecasts. Singular vectors for the ocean and coupled ocean–atmosphere system in order to understand the predictability of climate phenomena such as ENSO and meridional overturning circulation are reviewed and their potential use to initialize seasonal and decadal forecasts is considered. As stochastic parameterizations are being implemented, some speculations are made about the future of singular vectors for the predictability of weather and climate for theoretical applications and at the operational level.This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Lyapunov analysis: from dynamical systems theory to applications’.

Frequency Domain Multimodel Analysis of the Response of Atlantic Meridional Overturning Circulation to Surface Forcing

The dynamics of the Atlantic meridional overturning circulation (AMOC) vary considerably among different climate models; for example, some models show clear peaks in their power spectra while others do not. To elucidate these model differences, transfer functions are used to estimate the frequency domain relationship between surface forcing fields, including sea surface temperature, salinity, and wind stress, and the resulting AMOC response. These are estimated from the outputs of the Coupled Model Intercomparison Project phase 5 (CMIP5) and phase 3 (CMIP3) control runs for eightdifferent models,with a specificfocus on Geophysical Fluid Dynamics Laboratory Climate Model, version 2.1 (GFDL CM2.1), and the Community Climate System Model, version 4 (CCSM4), which exhibit rather different spectral behavior. The transfer functionsshowvery littleagreement amongmodelsforany ofthe pairsofvariablesconsidered, suggestingthe existence of systematic model errors and that considerable uncertainty in the simulation of AMOC in current climate models remains. However, a robust feature of the frequency domain analysis is that models with spectral peaks in their AMOC correspond to those in which AMOC variability is more strongly excited by high-latitude surface perturbations that have periods corresponding to the frequency of the spectral peaks. This explains why different models exhibit such different AMOC variability. These differences would not be evident without using a method that explicitly computes the frequency dependence rather than a priori assuming a particular functional form. Finally, transfer functions are used to evaluate two proposed physical mechanisms for model differences in AMOC variability: differences in Labrador Sea stratification and excitation by westward-propagating subsurface Rossby waves.

Optimal Surface Excitation of the Thermohaline Circulation

Abstract The amplification of thermohaline circulation (THC) anomalies resulting from heat and freshwater forcing at the ocean surface is investigated in a zonally averaged coupled ocean–atmosphere model. Optimal initial conditions of surface temperature and salinity leading to the largest THC growth are computed, and so are the structures of stochastic surface temperature and salinity forcing that excite maximum THC variance (stochastic optimals). When the THC amplitude is defined as its sum of squares (equivalent to using the standard L2 norm), the nonnormal linearized dynamics lead to an amplification with a time scale on the order of 100 yr. The optimal initial conditions have a vanishing THC anomaly, and the complex amplification mechanism involves the advection of both temperature and salinity anomalies by the mean flow and of the mean temperature and salinity by the anomaly flow. The L2 characterization of THC anomalies leads to physically interesting results, yet to a mathematically singular probl...

Oceanic Stochastic Parameterizations in a Seasonal Forecast System

AbstractStochastic parameterization provides a methodology for representing model uncertainty in ensemble forecasts. Here the impact on forecast reliability over seasonal time scales of three existing stochastic parameterizations in the ocean component of a coupled model is studied. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the stochastically perturbed parameterization tendency (SPPT) scheme, which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely, the western boundary currents and the Southern Ocean where ensemble spread is increased. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error on seasonal time scales. While there are good ground...