Determining Near‐Bottom Fluxes of Passive Tracers in Aquatic Environments

Bluteau, Cynthia; Ivey, Gregory; Donis, Daphné; Mcginnis, Daniel Frank

doi:10.1002/2017gl076789

Cited by 5 publications

(6 citation statements)

References 37 publications

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“…Classical turbulent boundary layer flows often exhibit logarithmic profiles with elevated shear at the boundary (e.g. Marusic et al 2013;Bluteau et al 2018), although the specific details of the flow vary with surface roughness, ambient stratification and external pressure gradients. While the profiles considered here differ from these classical boundary layers, we make this choice so as to facilitate comparison between our simulations and the isolated hyperbolic-tangent shear layer commonly studied in the KH literature.…”

Section: Summary and Discussionmentioning

confidence: 99%

The effects of boundary proximity on Kelvin–Helmholtz instability and turbulence

2023

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Studies of Kelvin–Helmholtz (KH) instability have typically modelled the initial flow as an isolated shear layer. In geophysical cases, however, the instability often occurs near boundaries and may therefore be influenced by boundary proximity effects. Ensembles of direct numerical simulations are conducted to understand the effect of boundary proximity on the evolution of the instability and the resulting turbulence. Ensemble averages are used to reduce sensitivity to small variations in initial conditions. Both the transition to turbulence and the resulting turbulent mixing are modified when the shear layer is near a boundary: the time scales for the onset of instability and turbulence are longer, and the height of the KH billow is reduced. Subharmonic instability is suppressed by the boundary because phase lock is prevented due to the diverging phase speeds of the KH and subharmonic modes. In addition, the disruptive influence of three-dimensional secondary instabilities on pairing is more profound as the two events coincide more closely. When the shear layer is far from the boundary, the shear-aligned convective instability is dominant; however, secondary central-core instability takes over when the shear layer is close to the boundary, providing an alternate route for the transition to turbulence. Both the efficiency of the resulting mixing and the turbulent diffusivity are dramatically reduced by boundary proximity effects.

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Section: Summary and Discussionmentioning

confidence: 99%

The effects of boundary proximity on Kelvin–Helmholtz instability and turbulence

2023

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“…This suggests that assuming either that dissipation is nearly constant or that it varies inversely with distance from the bottom has little effect on the estimate of K L . Note that a direct measurement of F might be made using near‐surface measurements of both velocity and dissolved oxygen, as described by Bluteau et al ().…”

Section: Discussionmentioning

confidence: 99%

Flow and Drag in a Seagrass Bed

et al. 2019

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We report direct measurement of drag forces due to tidal flow over a submerged seagrass bed in Ngeseksau Reef, Koror State, Republic of Palau. In our study, drag is computed using an array of high‐resolution pressure measurements, from which values of the drag coefficients, CD, referenced to measured depth‐averaged velocities, V, were inferred. Reflecting the fact that seagrass blades deflect in the presence of flow, we find that CD is O(1) when flows are weak and tends toward a value of 0.03 at the highest velocities, behavior that is consistent with existing theory for canopy flows with flexible canopy elements. A limited subset of velocity profiles obey the law of the wall, producing values of shear velocity that, while noisy, broadly agree with values inferred from the pressure measurements.

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“…This strategy enables the estimation of vertical fluxes for any parameter for which an accurate vertical gradient can be computed, provided K is known. There is no requirement to co-locate a fast-response sensor for the targeted parameter (e.g., oxygen) with a point-velocity sensor, which is the basis of existing "eddy correlation" field techniques (Pond et al, 1971;Lorrai et al, 2010;Bluteau et al, 2018). Now focusing on the right hand side of equation 2, the molecular dissipation of a tracer can also be described by c C , which is the rate of dissipation of tracer variance, or the rate at which fluctuations in the tracer are smoothed out:…”

Section: Ocean Color Ocean Soundmentioning

confidence: 99%

“…Applying eddy-correlation techniques to measurements from fast-sampling velocity-based instruments is the most direct way to obtain turbulent fluxes of a scalar (e.g., dissolved gases and salt). When paired with fast-response sensors such as dissolved oxygen (Bluteau et al, 2018) or temperature (Polzin et al, 2021), velocitybased instruments can be used to obtain turbulence quantities beyond ϵ and c, such as the velocity-fluctuations (i.e., Reynolds stresses) or turbulent fluxes (〈w ′ C ′ 〉). The scalar C ′ and the vertical velocities w ′ must be sampled sufficiently fast enough to resolve their time-averaged covariance over the flux-contributing time and length scales.…”

Section: Ocean Color Ocean Soundmentioning

confidence: 99%

“…Using vibration sensors and data processing algorithms has also reduced signal contamination from sources such as platform vibrations (Goodman et al, 2006). One can also rely on the larger scales of the microstructure subrange to estimate ϵ (Bluteau et al, 2016b) and c (Bluteau et al, 2018) to avoid vibration issues by sampling less rapidly. Furthermore, progress has been made in estimating the statistical uncertainty of a dissipation estimate and the quality of a spectrum objectively (Lueck, 2022a,b), which allows automated and reliable quality control of dissipation estimates.…”

Section: Microstructure-based Measurementsmentioning

confidence: 99%

See 1 more Smart Citation

Turbulent diapycnal fluxes as a pilot Essential Ocean Variable

Le Boyer,

Couto,

Alford

et al. 2023

Front. Mar. Sci.

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We contend that ocean turbulent fluxes should be included in the list of Essential Ocean Variables (EOVs) created by the Global Ocean Observing System. This list aims to identify variables that are essential to observe to inform policy and maintain a healthy and resilient ocean. Diapycnal turbulent fluxes quantify the rates of exchange of tracers (such as temperature, salinity, density or nutrients, all of which are already EOVs) across a density layer. Measuring them is necessary to close the tracer concentration budgets of these quantities. Measuring turbulent fluxes of buoyancy (Jb), heat (Jq), salinity (JS) or any other tracer requires either synchronous microscale (a few centimeters) measurements of both the vector velocity and the scalar (e.g., temperature) to produce time series of the highly correlated perturbations of the two variables, or microscale measurements of turbulent dissipation rates of kinetic energy (ϵ) and of thermal/salinity/tracer variance (χ), from which fluxes can be derived. Unlike isopycnal turbulent fluxes, which are dominated by the mesoscale (tens of kilometers), microscale diapycnal fluxes cannot be derived as the product of existing EOVs, but rather require observations at the appropriate scales. The instrumentation, standardization of measurement practices, and data coordination of turbulence observations have advanced greatly in the past decade and are becoming increasingly robust. With more routine measurements, we can begin to unravel the relationships between physical mixing processes and ecosystem health. In addition to laying out the scientific relevance of the turbulent diapycnal fluxes, this review also compiles the current developments steering the community toward such routine measurements, strengthening the case for registering the turbulent diapycnal fluxes as an pilot Essential Ocean Variable.

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Determining Near‐Bottom Fluxes of Passive Tracers in Aquatic Environments

Cited by 5 publications

References 37 publications

The effects of boundary proximity on Kelvin–Helmholtz instability and turbulence

The effects of boundary proximity on Kelvin–Helmholtz instability and turbulence

Flow and Drag in a Seagrass Bed

Turbulent diapycnal fluxes as a pilot Essential Ocean Variable

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