On low-frequency variability of the midlatitude ocean gyres

Shevchenko, Igor; Berloff, Pavel; Guerrero-Lopez, David; Román, José E.

doi:10.1017/jfm.2016.208

Cited by 19 publications

(15 citation statements)

References 34 publications

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“…at reference model parameters [8] is characterized by a robust large-scale decadal low-frequency variability (LFV) at ≈17 years and involving coherent meridional shifts of the eastward jet extension separating the gyres. This LFV is driven by transient mesoscale eddies, qualitatively similar to the turbulent oscillator studied by [60,61]; see [62][63][64][65][66][67][68] for alternative theories. Still, there is no clear scale separation between the eddies and large-scale flow, and in fact, the LFV accounts for a relatively small fraction of the total variability, as demonstrated below in the detailed DAH analysis.…”

Section: Oceanic Datasetsupporting

confidence: 64%

Multiscale Stuart-Landau Emulators: Application to Wind-Driven Ocean Gyres

Kondrashov

Chekroun

Berloff

2018

Fluids

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The multiscale variability of the ocean circulation due to its nonlinear dynamics remains a big challenge for theoretical understanding and practical ocean modeling. This paper demonstrates how the data-adaptive harmonic (DAH) decomposition and inverse stochastic modeling techniques introduced in (Chekroun and Kondrashov, (2017), Chaos, 27), allow for reproducing with high fidelity the main statistical properties of multiscale variability in a coarse-grained eddy-resolving ocean flow. This fully-data-driven approach relies on extraction of frequency-ranked time-dependent coefficients describing the evolution of spatio-temporal DAH modes (DAHMs) in the oceanic flow data. In turn, the time series of these coefficients are efficiently modeled by a family of low-order stochastic differential equations (SDEs) stacked per frequency, involving a fixed set of predictor functions and a small number of model coefficients. These SDEs take the form of stochastic oscillators, identified as multilayer Stuart-Landau models (MSLMs), and their use is justified by relying on the theory of Ruelle-Pollicott resonances. The good modeling skills shown by the resulting DAH-MSLM emulators demonstrates the feasibility of using a network of stochastic oscillators for the modeling of geophysical turbulence. In a certain sense, the original quasiperiodic Landau view of turbulence, with the amendment of the inclusion of stochasticity, may be well suited to describe turbulence.

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Section: Oceanic Datasetsupporting

confidence: 64%

Multiscale Stuart-Landau Emulators: Application to Wind-Driven Ocean Gyres

Kondrashov

Chekroun

Berloff

2018

Fluids

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“…Specific modes of variability have been identified in various idealized ocean models. A turbulent oscillator mode was proposed by Berloff et al (2007b) with a rough time scale of 12 years, and has been found in other quasigeostrophic models as well (e.g., Shevchenko et al 2016). This mode is characterized by changes to the magnitude and position of the oceanic jet in the western boundary current separation region.…”

Section: Introductionmentioning

confidence: 65%

Frequency-Domain Analysis of the Energy Budget in an Idealized Coupled Ocean–Atmosphere Model

et al. 2020

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Climate variability is investigated by identifying the energy sources and sinks in an idealized, coupled, ocean–atmosphere model, tuned to mimic the North Atlantic region. The spectral energy budget is calculated in the frequency domain to determine the processes that either deposit energy into or extract energy from each fluid, over time scales from one day up to 100 years. Nonlinear advection of kinetic energy is found to be the dominant source of low-frequency variability in both the ocean and the atmosphere, albeit in differing layers in each fluid. To understand the spatial patterns of the spectral energy budget, spatial maps of certain terms in the spectral energy budget are plotted, averaged over various frequency bands. These maps reveal three dynamically distinct regions: along the western boundary, the western boundary current separation, and the remainder of the domain. The western boundary current separation is found to be a preferred region to energize oceanic variability across a broad range of time scales (from monthly to decadal), while the western boundary itself acts as the dominant sink of energy in the domain at time scales longer than 50 days. This study paves the way for future work, using the same spectral methods, to address the question of forced versus intrinsic variability in a coupled climate system.

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“…Also a small set of modes should be sufficient in order to assure feasibility. However, dynamical modes are typically constructed via generalized eigenproblems (e.g., linear instability modes; Dijkstra 2005;Berloff 2005b;Shevchenko et al 2016) or optimization problems (e.g., Lyapunov vectors, CNOPs; Dijkstra 2013; Dijkstra and Viebahn 2015) and, hence, are generally expensive to compute, if at all.…”

Section: Dynamical Spatial Mode Representation Of the Eddy Forcingmentioning

confidence: 99%

“…In this case, the LFV is not a single-mode pattern, but rather a coherent pattern phenomenon consisting of a large number of short period phase-related eigenmodes interacting with each other. We note that this can apply to both (high resolution) statistical eigenmodes like EOFs (Gille and Kelly 1996) and linear eigenmodes on a background flow (Shevchenko et al 2016). Obviously, the small-scale structures of the dynamical modes are not resolvable on a low-resolution model grid.…”

Section: Introductionmentioning

confidence: 97%

“…The lack of scale separation in space implies that the dynamical modes are multiscale patterns both in the horizontal and vertical directions. For example, for the midlatitude ocean gyres it is found that due to the background flow most eigenmodes contain a large variety of scales (Shevchenko et al 2016). In this case, the LFV is not a single-mode pattern, but rather a coherent pattern phenomenon consisting of a large number of short period phase-related eigenmodes interacting with each other.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Toward a Turbulence Closure Based on Energy Modes

Viebahn

Crommelin

Dijkstra

2019

Journal of Physical Oceanography

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A new approach to parameterizing subgrid-scale processes is proposed: The impact of the unresolved dynamics on the resolved dynamics (i.e., the eddy forcing) is represented by a series expansion in dynamical spatial modes that stem from the energy budget of the resolved dynamics. It is demonstrated that the convergence in these so-called energy modes is faster by orders of magnitude than the convergence in Fourier-type modes. Moreover, a novel way to test parameterizations in models is explored. The resolved dynamics and the corresponding instantaneous eddy forcing are defined via spatial filtering that accounts for the representation error of the equations of motion on the low-resolution model grid. In this way, closures can be tested within the high-resolution model, and the effects of different parameterizations related to different energy pathways can be isolated. In this study, the focus is on parameterizations of the baroclinic energy pathway. The corresponding standard closure in ocean models, the Gent–McWilliams (GM) parameterization, is also tested, and it is found that the GM field acts like a stabilizing direction in phase space. The GM field does not project well on the eddy forcing and hence fails to excite the model’s intrinsic low-frequency variability, but it is able to stabilize the model.

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On low-frequency variability of the midlatitude ocean gyres

Cited by 19 publications

References 34 publications

Multiscale Stuart-Landau Emulators: Application to Wind-Driven Ocean Gyres

Multiscale Stuart-Landau Emulators: Application to Wind-Driven Ocean Gyres

Frequency-Domain Analysis of the Energy Budget in an Idealized Coupled Ocean–Atmosphere Model

Toward a Turbulence Closure Based on Energy Modes

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