Global Estimates of the Energy Transfer From the Wind to the Ocean, With Emphasis on Near‐Inertial Oscillations

Abstract

Estimates of the kinetic energy transfer from the wind to the ocean are often limited by the spatial and temporal resolution of surface currents and surface winds. Here we examine the wind work in a pair of global, very high‐resolution (1/48° and 1/24°) MIT general circulation model simulations in Latitude‐Longitude‐polar Cap (LLC) configuration that provide hourly output at spatial resolutions of a few kilometers and include tidal forcing. A cospectrum analysis of wind stress and ocean surface currents shows positive contribution at large scales (>300 km) and near‐inertial frequency and negative contribution from mesoscales, tidal frequencies, and internal gravity waves. Larger surface kinetic energy fluxes are in the Kuroshio in winter at large scales (40 mW/m2) and mesoscales (−30 mW/m2). The Kerguelen region is dominated by large scale (∼20 mW/m2), followed by inertial oscillations in summer (13 mW/m2) and mesoscale in winter (−12 mW/m2). Kinetic energy fluxes from internal gravity waves (−0.1 to −9.9 mW/m2) are generally stronger in summer. Surface kinetic energy fluxes in the LLC simulations are 4.71 TW, which is 25–85% higher than previous global estimates from coarser (1/6–1/10°) general ocean circulation models; this is likely due to improved representation of wind variability (6‐hourly, 0.14°, operational European Center for Medium‐Range Weather Forecasts). However, the low wind power input to the near‐inertial frequency band obtained with LLC (0.16 TW) compared to global slab models suggests that wind variability on time scales less than 6 hr and spatial scales less than 15 km are critical to better representing the wind power input in ocean circulation models.

Determining the dependence of the power supply to the ocean on the length and time scales of the dynamics between the meso-scale and the synoptic scale, from satellite data

“…This indicates that higher resolutions in space and time are necessary to estimate the power fluxes into the ocean mixed layer and that we do not know at which scales we possibly observe convergence. This agrees with a key point in [25], who state that small scales in space and short times are critical to better representing wind power input in general circulation models. Furthermore, we do not know to what extent the power input due to the dynamics at a certain scale in time and space contributes to climate relevant processes and how they can be parameterized.…”

“…They also note that the increase is dominated by the temporal scales over spatial scales due to the resonance condition at the inertial frequency. An increased power input due to higher frequency winds was also found in the numerical experiments of [22] and [25]. It points towards the fact that at short times there is a strong correlation between the ocean currents near the surface and the surface winds.…”

“…Eddy-killing is not restricted to eddies, its quantification over a large range of scales in space and time is considered here. For a detailed discussion on the importance of scales in space-and-time for the power input to the ocean and the physical processes involved, I refer the reader to the recent work by [25], who investigated the problem based on model results.…”

Energetic Submesoscale Dynamics in the Ocean Interior

“…The v-k cospectra of vertical heat fluxes are computed similar to the v-k spectrum, following the method described in Flexas et al (2019). First, the Fourier transforms of vertical velocityŴ(k, l, v) and temperaturê T(k, l, v) are calculated.…”

The Vertical Structure of Open-Ocean Submesoscale Variability during a Full Seasonal Cycle

“…Another possibility is that internal waves drain a significant amount of energy from submesoscale balanced flow (e.g. Taylor and Straub (2016); Barkan et al (2017); Xie and Vanneste (2015); Rocha et al (2018)), an effect that would be underestimated in the model because the internalwave field-particularly the near-inertial component-is unrealistically weak (Figures 5, 6), probably as a result from the relatively coarse (6 hour) wind variability (Yu et al 2019b;Flexas et al 2019).…”