Decadal variability of wind-energy input to the world ocean

Huang, Rui Xin; Wang, Wei; Liu, Ling Ling

doi:10.1016/j.dsr2.2005.11.001

Cited by 83 publications

(72 citation statements)

References 22 publications

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“…where hÁi represents the global average at a selected depth level, N 2 (z) is the temporally and globally averaged buoyancy frequency (Huang 2010), and S and u represent salinity and potential temperature at time t and position (x, y, z). Here, r*(x, y, z, t) 5 r(x, y, z, t) 2 hr(x, y, z, t)i.…”

Section: Formulation Of the Time-dependent Energy Diagrammentioning

confidence: 99%

“…In contrast to the atmosphere acting as a heat engine (Oort and Peixóto 1983), the ocean is largely wind driven: the total power input into the ocean is 6.6 TW, of which 4.1 TW is wind power input (von Storch et al 2012). The wind power input undergoes significant temporal variability (Huang et al 2006), and not surprisingly, EKE levels show a sensitivity to this wind variability. For example, in regions with substantial wind energy, eddy variability is well correlated with the wind forcing magnitude on annual and interannual time scales (Stammer and Wunsch 1999).…”

Section: Introductionmentioning

confidence: 99%

“…We chose a widely used QG definition of available potential energy (APE; e.g., Pedlosky 1987;Oort et al 1989Oort et al , 1994Huang 2010;Brown and Fedorov 2010). The total APE of the full flow field P T is…”

Section: Formulation Of the Time-dependent Energy Diagrammentioning

confidence: 99%

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Time-Dependent Eddy-Mean Energy Diagrams and Their Application to the Ocean

Chen

Thompson

Flierl

2016

Journal of Physical Oceanography

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Insight into the global ocean energy cycle and its relationship to climate variability can be gained by examining the temporal variability of eddy-mean flow interactions. A time-dependent version of the Lorenz energy diagram is formulated and applied to energetic ocean regions from a global, eddying state estimate. The total energy in each snapshot is partitioned into three components: energy in the mean flow, energy in eddies, and energy temporal anomaly residual, whose time mean is zero. These three terms represent, respectively, correlations between mean quantities, correlations between eddy quantities, and eddy-mean correlations. Eddy-mean flow interactions involve energy exchange among these three components. The temporal coherence about energy exchange during eddy-mean flow interactions is assessed. In the Kuroshio and Gulf Stream Extension regions, a suppression relation is manifested by a reduction in the baroclinic energy pathway to the eddy kinetic energy (EKE) reservoir following a strengthening of the barotropic energy pathway to EKE; the baroclinic pathway strengthens when the barotropic pathway weakens. In the subtropical gyre and Southern Ocean, a delay in energy transfer between different reservoirs occurs during baroclinic instability. The delay mechanism is identified using a quasigeostrophic, two-layer model; part of the potential energy in large-scale eddies, gained from the mean flow, cascades to smaller scales through eddy stirring before converting to EKE. The delay time is related to this forward cascade and scales linearly with the eddy turnover time. The relation between temporal variations in wind power input and eddy-mean flow interactions is also assessed.

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Section: Formulation Of the Time-dependent Energy Diagrammentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Time-Dependent Eddy-Mean Energy Diagrams and Their Application to the Ocean

Chen

Thompson

Flierl

2016

Journal of Physical Oceanography

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“…Following Wunsch [1998], Huang et al [2006], and Zhai et al [2012], the rate of wind energy input to the surface currents is calculated by the scalar product of wind stress and surface current velocity :…”

Section: Modelmentioning

confidence: 99%

Eddy energy sources and sinks in the South China Sea

Yang

Liu

et al. 2013

JGR Oceans

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[1] The eddy energy sources and sinks in the South China Sea (SCS) are studied based on a high-resolution ocean circulation model. Eddies are found to acquire their energy from barotropic instability (BT), the release of available potential energy (APE) associated with baroclinic instability (BC) and horizontal convergence from surrounding areas, while they lose energy due to turbulent processes. Both the eddy energy sources and sinks show western intensification with their maximum around the southwestern SCS where most of the wind-input energy occurs, and the Luzon Strait where the Kuroshio intrudes the SCS in winter. Unlike that in the open ocean, the eddy energy in the inner SCS is confined to the upper layer. Besides, the eddy energy indicates clear seasonal variability, especially at the Luzon Strait where the eddy activity is much stronger in winter than in summer. Energy budget analysis suggests that APE releasing is found to be the most important eddy energy source, accounting for over 60% of the total, followed by energy convergence from surrounding areas in horizontal direction (around 20%) and energy released from BT (around 15%). Most of the generated energy is mainly balanced by the turbulent processes, while both of the downward energy flux and tendency term are negligible.

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“…A general discussion of atmospheric wind structures can be found in Thompson and Wallace (2000) and Thompson et al (2000). Huang et al (2006) showed an apparent increase of 12% in the rate of working of the wind (as depicted by the NCEP-NCAR reanalysis) over the 25 yr beginning in 1980. To the extent that there exist trends in the zonal wind stress in the 15-yr period used here, they are a sum of spatially complicated structures in the higher EOFs (not shown).…”

Section: February 2009 W U N S C H a N D H E I M B A C Hmentioning

confidence: 99%

The Global Zonally Integrated Ocean Circulation, 1992–2006: Seasonal and Decadal Variability

Wunsch

Heimbach

2009

Journal of Physical Oceanography

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The zonally integrated meridional and vertical velocities as well as the enthalpy transports and fluxes in a least squares adjusted general circulation model are used to estimate the top-to-bottom oceanic meridional overturning circulation (MOC) and its variability from 1992 to 2006. A variety of simple theories all produce time scales suggesting that the mid-and high-latitude oceans should respond to atmospheric driving only over several decades. In practice, little change is seen in the MOC and associated heat transport except very close to the sea surface, at depth near the equator, and in parts of the Southern Ocean. Variability in meridional transports in both volume and enthalpy is dominated by the annual cycle and secondarily by the semiannual cycle, particularly in the Southern Ocean. On time scales longer than a year, the solution exhibits small trends with complicated global spatial patterns. Apart from a net uptake of heat from the atmosphere (forced by the NCEP-NCAR reanalysis, which produces net ocean heating), the origins of the meridional transport trends are not distinguishable and are likely a combination of model disequilibrium, shifts in the observing system, other trends (real or artificial) in the meteorological fields, and/or true oceanic secularities. None of the results, however, supports an inference of oceanic circulation shifts taking the system out of the range in which changes are more than small perturbations. That the oceanic observations do not conflict with an apparent excess heat uptake from the atmosphere implies a continued undersampling of the global ocean, even in the upper layers.

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Decadal variability of wind-energy input to the world ocean

Cited by 83 publications

References 22 publications

Time-Dependent Eddy-Mean Energy Diagrams and Their Application to the Ocean

Time-Dependent Eddy-Mean Energy Diagrams and Their Application to the Ocean

Eddy energy sources and sinks in the South China Sea

The Global Zonally Integrated Ocean Circulation, 1992–2006: Seasonal and Decadal Variability

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