Measuring Turbulent Dissipation Using a Tethered ADCP

Lucas, Natasha; Simpson, John H.; Rippeth, Tom P.; Old, Chris

doi:10.1175/jtech-d-13-00198.1

Cited by 34 publications

(32 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…L O , however, increases with e 1=2 so that, at times of significant dissipation, our sampling interval of 5-8 cm should have been adequate. The convincing fits of SF to the r 2=3 form shown in Lucas et al (2014) support this inference.…”

Section: Simpson Et Almentioning

confidence: 62%

“…Whereas previous ADCP measurements of e in lakes have utilised instruments fixed on a frame sitting on the lake bed, the observations reported here also include data from an ADCP mounted on a buoyant float in mid-water. This mode of operation on a tethered buoy has recently been validated by comparison with a Vertical Microstructure Profiler (VMP) shear probe measurements (Lucas et al 2014) which demonstrated that the motions of the tethered buoy do not compromise the estimation of e because the SF method is based on velocity differences which are not significantly affected by buoy motion. These measurements also confirmed the validity of the constant C v 5 1.45, originally determined from Doppler radar measurements of turbulence in the atmosphere (Sauvageot 1992), for dissipation measurements in water.…”

Section: Dissipation Via the Structure Functionmentioning

confidence: 96%

See 1 more Smart Citation

Dissipation and mixing during the onset of stratification in a temperate lake, W indermere

et al. 2014

View full text Add to dashboard Cite

Acoustic Doppler Current Profilers and chains of temperature sensors were used to observe the spring transition to stable stratification over a 55-d period in a temperate lake. Observations of the flow structure were complemented by measurements of dissipation, based on the structure function method, near the lake bed and in the upper part of the water column. During complete vertical mixing, wind-driven motions had horizontally isotropic velocities with roughly equal barotropic and baroclinic kinetic energy. Dissipation was closely correlated with the wind-speed cubed, indicating law of the wall scaling, and had peak values of $ 1 3 10 25.5 W kg 21 at ten meters depth during maximum wind forcing (W $ 15 m s 21 ). As stratification developed, the flow evolved into a predominantly baroclinic regime dominated by the first mode internal seiche, with root mean square axial flow speeds of $ 2-3 cm 21 ; $ 2.5-times the transverse component. At 2.8 m above the bed, most of the dissipation occurred in a number of strong maxima coinciding with peaks of near-bed flow. In the pycnocline, dissipation was low most of the time, but with pronounced maxima (reaching $ 1 3 10 25 W kg 21 ) closely related to the local velocity shear. The downward diffusive heat flux across the pycnocline over 27.5 d accounted for $ 70% of the temperature rise in the water column below. Total lake kinetic energy increased by a factor of three between mixed and stratified regimes, in spite of reduced wind forcing, indicating less efficient damping in stable conditions.

show abstract

Section: Simpson Et Almentioning

confidence: 62%

Section: Dissipation Via the Structure Functionmentioning

confidence: 96%

Dissipation and mixing during the onset of stratification in a temperate lake, W indermere

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Above 0.7 m elevation, stress estimates became intermittent, with mostly small values punctuated by occasional high‐intensity bursts (e.g., days 156.7 and 158.2, Figures e and f). At these high ( z > 0.7 m) elevations, structure functions [ Wiles et al ., ; Lucas et al ., ] revealed occasional bursts of high‐velocity variance at small (0.015–0.045 m) scales (not shown). These observations might indicate flow disturbance by instruments or the tripod, casting doubt on stresses measured above z = 0.7 m.…”

Section: Overview Of Observationsmentioning

confidence: 99%

Turbulent production in an internal wave bottom boundary layer maintained by a vertically propagating seiche

Henderson

2016

JGR Oceans

View full text Add to dashboard Cite

Internal seiches, which supply the energy responsible for mixing many lakes, are often modeled as vertically standing waves. However, recent observations of vertical seiche propagation in a small lake are inconsistent with the standard, vertically standing model. To examine the processes responsible for such propagation, drag and turbulent production in the bottom boundary layer of a small lake are related to the energy supplied by a propagating seiche (period 10–24 h). Despite complex and fluctuating stratification, which often inhibited mixing within 0.4 m of the bed, bottom stress was well represented by a simple drag coefficient model (drag coefficient 1.5 × 10−3). The net supply of seiche energy to the boundary layer was estimated by fitting a model for internal wave vertical propagation to velocity profiles measured above the boundary layer (1–4.5 m above lakebed). Fitted reflection coefficients ranged from 0.3 at 1 cycle/d frequency to 0.7 at 2.4 cycles/d (cf. near‐unity coefficients of classical seiche theories). The net supply of seiche energy approximately balanced boundary layer turbulent production. Three of four peaks in production and energy flux occurred 0.8–2.2 days after strong oscillating winds, a delay comparable to the time required for seiche energy to propagate to the lakebed. A model based on the estimated drag coefficient predicted the observed frequency dependence of the seiche reflection coefficient. For flat‐bed regions in narrow lakes, the model predicts that reflection is controlled by the ratio of water velocity to vertical wave propagation speed, with sufficiently large ratios leading to weak reflection, and clear vertical seiche propagation.

show abstract

“…Structure functions provide spectral information about a range of timescales, as opposed to l and L which provide single correlation scales. Spatial structure functions have also been used to infer energy dissipation rates, as done in Wiles et al [47], Thomson et al [15] and Lucas et al [48]. Fig.…”

Section: Temporal Structure Functionsmentioning

confidence: 99%

Characterization of turbulence anisotropy, coherence, and intermittency at a prospective tidal energy site: Observational data analysis

et al. 2015

View full text Add to dashboard Cite

a b s t r a c tAs interest in marine renewable energy increases, observations are crucial for understanding the environments that prospective turbines will encounter. Data from an acoustic Doppler velocimeter in Puget Sound, WA are used to perform a detailed characterization of the turbulent flow encountered by a turbine in a tidal strait. Metrics such as turbulence intensity, structure functions, probability density functions, intermittency, coherent turbulence kinetic energy, anisotropy invariants, and a new scalar measure of anisotropy are used to characterize the turbulence. The results indicate that the scalar anisotropy magnitude can be used to identify and parameterize coherent, turbulent events in the flow. An analysis of the anisotropy characteristics leads to a physical description of turbulent stresses as being primarily one-or two-dimensional, in contrast to isotropic, three-dimensional turbulence. A new measure of the anisotropy magnitude is introduced to quantify the level of anisotropic, coherent turbulence in a coordinate-independent way. These diagnostics and results will be useful for improved realism in modeling the performance and loading of turbines in realistic ocean environments.

show abstract

Measuring Turbulent Dissipation Using a Tethered ADCP

Cited by 34 publications

References 37 publications

Dissipation and mixing during the onset of stratification in a temperate lake, W indermere

Dissipation and mixing during the onset of stratification in a temperate lake, W indermere

Turbulent production in an internal wave bottom boundary layer maintained by a vertically propagating seiche

Characterization of turbulence anisotropy, coherence, and intermittency at a prospective tidal energy site: Observational data analysis

Contact Info

Product

Resources

About