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Abstract. Use of an ocean parameter and state estimation framework – such as the Estimating the Circulation and Climate of the Ocean (ECCO) framework – could provide an opportunity to learn about the spatial distribution of the diapycnal diffusivity parameter (κρ) that observations alone cannot due to gaps in coverage. However, we show that the inclusion of misfits to observed physical variables – such as in situ temperature, salinity, and pressure – currently accounted for in ECCO is not sufficient, as κρ from ECCO does not agree closely with any observationally derived product. These observationally derived κρ products were inferred from microstructure measurements, derived from Argo and conductivity–temperature–depth (CTD) data using a strain-based parameterization of fine-scale hydrographic structure, or calculated from climatological and seafloor data using a parameterization of tidal mixing. The κρ products are in close agreement with one another but have both measurement and structural uncertainties, whereas tracers can have relatively small measurement uncertainties. With the ultimate goal being to jointly improve the ECCO state estimate and representation of κρ in ECCO, we investigate whether adjustments in κρ due to inclusion of misfits to a tracer – dissolved oxygen concentrations from an annual climatology – would be similar to those due to inclusion of misfits to observationally derived κρ products. We do this by performing sensitivity analyses with ECCO. We compare multiple adjoint sensitivity calculations: one configuration uses misfits to observationally derived κρ, and the other uses misfits to observed dissolved oxygen concentrations. We show that adjoint sensitivities of dissolved oxygen concentration misfits to the state estimate's control space typically direct κρ to improve relative to the observationally derived values. These results suggest that the inclusion of oxygen in ECCO's misfits will improve κρ in ECCO, particularly in (sub)tropical regions. 

Abstract The ocean is home to many different submesoscale phenomena, including internal waves, fronts, and gravity currents. Each of these processes entail complex nonlinear dynamics, even in isolation. Here we present shipboard, moored, and remote observations of a submesoscale gravity current front created by a shoaling internal tidal bore in the coastal ocean. The internal bore is observed to flatten as it shoals, leaving behind a gravity current front that propagates significantly slower than the bore. We posit that the generation and separation of the front from the bore is related to particular stratification ahead of the bore, which allows the bore to reach the maximum possible internal wave speed. After the front is calved from the bore, it is observed to propagate as a gravity current for ≈4 hours, with associated elevated turbulent dissipation rates. A strong cross-shore gradient of along-shore velocity creates enhanced vertical vorticity (Rossby number ≈ 40) that remains locked with the front. Lateral shear instabilities develop along the front and may hasten its demise. 

A reduced‐physics model is employed at 1/25° to 1/100° global resolution to determine (a) if linear dynamics can reproduce the observed low‐mode M₂internal tide, (b) internal‐tide sensitivity to bathymetry, stratification, surface tides, and dissipation parameterizations, and (c) the amount of power transferred to the nonstationary internal tide. The simulations predict 200 GW of mode‐1 internal‐tide generation, consistent with a general circulation model and semianalytical theory. Mode‐1 energy is sensitive to damping, but a simulation using parameterizations for wave drag and wave‐mean interaction predicts 84% of satellite observed sea‐surface height amplitude variance on a 1° × 1° grid. The simulation energy balance indicates that 16% of stationary mode‐1 energy is scattered to modes 2–4 and negligible energy propagates onto the shelves. The remaining 84% of energy is lost through parameterizations for high‐mode scattering over rough topography (54%) and wave‐mean interactions that transfer energy to the nonstationary internal tide (29%).

 

Turbulent mixing in the ocean is key to regulate the transport of heat, freshwater and biogeochemical tracers, with strong implications for Earth’s climate. In the deep ocean, tides supply much of the mechanical energy required to sustain mixing via the generation of internal waves, known as internal tides, whose fate—the relative importance of their local versus remote breaking into turbulence—remains uncertain. Here, we combine a semi-analytical model of internal tide generation with satellite and in situ measurements to show that from an energetic viewpoint, small-scale internal tides, hitherto overlooked, account for the bulk (>50%) of global internal tide generation, breaking and mixing. Furthermore, we unveil the pronounced geographical variations of their energy proportion, ignored by current parameterisations of mixing in climate-scale models. Based on these results, we propose a physically consistent, observationally supported approach to accurately represent the dissipation of small-scale internal tides and their induced mixing in climate-scale models.

 

The potential influences of turbulence on planktonic processes such as nutrient uptake, grazing, predation, infection, and mating have been explored in hundreds of laboratory and theoretical studies. However, the turbulence levels used may not represent those experienced by oceanic plankton, bringing into question their relevance for understanding planktonic dynamics in the ocean. Here, we take a data‐centric approach to understand the turbulence climate experienced by plankton in the ocean, analyzing over one million turbulence measurements acquired in the open ocean. Median dissipation rates in the upper 100 m were < 10⁻⁸ W kg⁻¹, with 99% of the observations < 10⁻⁶ W kg⁻¹. Below mixed layers, the median dissipation rate was ~ 10⁻¹⁰ W kg⁻¹, with 99% of the observations < 10⁻⁷ W kg⁻¹. Even in strongly mixing layers the median dissipation rates rarely reached 10⁻⁵ W kg⁻¹, decreasing by orders of magnitude over 10 m or less in depth. Furthermore, episodes of intense turbulence were transient, transitioning to background levels within 10 min or less. We define three turbulence conditions in the ocean: weak (< 10⁻⁸ W kg⁻¹), moderate (10⁻⁸–10⁻⁶ W kg⁻¹), and strong (> 10⁻⁶ W kg⁻¹). Even the strongest of these is much weaker than those used in most laboratory experiments. The most frequent turbulence levels found in this study are weak enough for most plankton—including small protists—to outswim them, and to allow chemical plumes and trails to persist for tens of minutes. Our analyses underscore the primary importance of planktonic behavior in driving individual interactions.