Hemantha W. Wijesekera

The Application of Internal-Wave Dissipation Models to a Region of Strong Mixing

Abstract Several models now exist for predicting the dissipation rate of turbulent kinetic energy, ϵ, in the oceanic thermocline as a function of the large-scale properties of the internal gravity wave field. These models are based on the transfer of energy toward smaller vertical scales by wave-wave interactions, and their predictions are typically evaluated for a canonical internal wave field as described by Garrett and Munk. Much of the total oceanic dissipation may occur, however, in regions where the wave field deviates in some way from the canonical form. In this paper simultaneous measurements of the internal wave field and ϵ from a drifting ice camp in the eastern Arctic Ocean are used to evaluate the efficacy of existing models in a region with an anomalous wave field and energetic mixing. By explicitly retaining the vertical wavenumber bandwidth parameter, β*, models can still provide reasonable estimates of the dissipation rate. The amount of data required to estimate β*, is, however, substanti...

Surface layer response to weak winds, westerly bursts, and rain squalls in the western Pacific warm pool

In November–December 1992, we measured microstructure, the hydrographic field, and the velocity field in the western equatorial Pacific near 1°43′S and 156°E as the first part of the Tropical Ocean - Global Atmosphere - Coupled Ocean Atmosphere Response Experiment. During our stay, we observed two westerly wind bursts with maximum speeds of about 10 m s−1, rainfalls of about 20 mm h−1, and nearly 2 weeks of calm and dry weather. During wind bursts, mixing in the upper 1 MPa was dramatic and rapid, and the major turbulence in the thermocline was produced by near-inertial shears following the wind bursts, during which dissipation rates and Richardson numbers were comparable to those in the central Pacific. By the end of the October–November westerly burst, the averaged eddy diffusivity of momentum in the mixed layer was about 10−2 m2 s−1. Below the mixed layer, a layer about 0.50–0.75 MPa thick with high shear and strain along with a high dissipation rate persisted even after the wind burst. During calm days, mixing was primarily driven by nighttime convection and was confined to the upper 0.1 or 0.2 MPa. In general, no diurnal deep cycle in dissipation rate was found below the mixed layer, unlike in the central equatorial Pacific. Entrainment below the mixed layer occurred when both wind work and convection were large. On average, the entrainment heat flux at the base of the mixed layer was about 6 (±2) W m−2. Salinity gradients were important to density between 0.3 and 0.6 MPa. However, the salinity stratification did not control entrainment mixing. During calm and dry weather, the mixed layer heat content was governed by the vertical divergence of the radiative flux, that is, the net surface heat flux minus the radiative flux out the bottom of the layer. Both the entrainment flux and the advective flux (which was estimated as the residual term) were smaller than uncertainties in the surface heat flux. During the October–November wind burst, however, the advective term was one of the most dominant terms in the heat budget. Although the entrainment heat flux was small over short timescales, it may be important in long-term budgets because the long-term net surface heating could also be small.

Upper-Ocean Turbulence during a Westerly Wind Burst: A Comparison of Large-Eddy Simulation Results and Microstructure Measurements

The response of the upper ocean to westerly wind forcing in the western equatorial Pacific was modeled by means of large-eddy simulation for the purpose of comparison with concurrent microstructure observations. The model was initialized using currents and hydrography measured during the Coupled Ocean‐Atmosphere Response Experiment (COARE) and forced using measurements of surface fluxes over a 24-h period. Comparison of turbulence statistics from the model with those estimated from concurrent measurements reveals good agreement within the mixed layer. The shortcomings of the model appear in the stratified fluid below the mixed layer, where the vertical length scales of turbulent eddies are limited by stratification and are not adequately resolved by the model. Model predictions of vertical heat and salt fluxes in the entrainment zone at the base of the mixed layer are very similar to estimates based on microstructure data.

Modeling study of turbulent mixing over the continental shelf: Comparison of turbulent closure schemes

limitation is imposed. During upwelling-favorable winds, the majority of turbulent mixing occurs in the top and the bottom boundary layers and in the vicinity of the vertically and horizontally sheared coastal jet. Turbulent mixing in the coastal jet is primarily driven by shear-production. The near-surface flow on the inner shelf becomes convectively unstable as wind stress forces the upwelled water to flow offshore in the surface layer. During downwelling-favorable winds, the strongest mixing occurs in the vicinity of the downwelling front. The largest turbulent kinetic energy and dissipation are found near the bottom of the front. Turbulence in the bottom boundary layer offshore of the front is concentrated between recirculation cells which are generated as a result of symmetric instabilities in the boundary layer flow. INDEX TERMS: 4219 Oceanography: General: Continental shelf processes; 4568 Oceanography: Physical: Turbulence, diffusion, and mixing processes; 4255 Oceanography: General: Numerical modeling; 4279 Oceanography: General: Upwelling and convergences;

Internal waves and mixing in the upper equatorial Pacific Ocean

Microstructure measurements in the equatorial Pacific at 140°W in late 1984 show a pronounced diurnal variation in both high-frequency internal wave energy and kinetic energy dissipation rate. Observations indicated that after sunset, internal waves (presumably generated by convective overturns in the mixed layer) propagate downward and increase turbulence levels in the pycnocline. It is proposed that large mixed layer eddies in the South Equatorial Current interact with the large shear caused by the Equatorial Undercurrent to generate a westward going anisotropic wave field. The momentum transport in the radiated wave field results in a drag force on the equatorial mean flow field. The observed mean wind stress at 140°W during Tropic Heat I (which is twice as large as the annual mean wind) is closer to the estimated radiation stress (∼−10−4 m2 s−2) at the base of the mixed layer (≈30 m) than to the estimated turbulent stress (∼−10−5 m2 s−2). A wave dissipation model based on the observed turbulent kinetic energy dissipation rate is introduced in order to estimate the wave momentum flux divergence in the stratified region above the undercurrent core. The model predicts that most of the downward wave momentum flux penetrates through the undercurrent core. It is hypothesized that when the wind stress is strong, the equatorial Pacific Ocean responds by generating a westward traveling internal wave field which transports much of the surface wind stress below the actively mixing surface layer.

Shannon entropy as an indicator of age for turbulent overturns in the oceanic thermocline

The Shannon entropy is a measure of the degree of intricacy contained in any graphable n-dimensional realization of an observable quantity. We use the Shannon entropy to measure the intricacy of density overturns in the oceanic thermocline and find that the Shannon entropy is related to the Thorpe scale LT [Thorpe, 1977] and the Ozmidov scale LO [Ozmidov, 1965]. We find that (1) small Shannon entropy corresponds to small values of ROT (≡LO/LT), while large Shannon entropy is associated with large values of ROT; (2) density spectra are typically more steep than inertial subrange spectra when both Shannon entropy and ROT are small, whereas the spectral slope tends to be flatter than inertial subrange spectra when both Shannon entropy and ROT are large; (3) the Grashof number is very large (O(1010)) when Shannon entropy is small, indicating that these patches are extremely density unstable; (4) spectral bandwidth is much larger for patches with small Shannon entropy than for those with large entropy, indicating that large-scale, or “bulk” Reynolds number is large when entropy is small. We discuss the hypothesis that the degree of intricacy, and hence the Shannon entropy, increases with increasing time in a turbulent overturn and is observed to decrease only when the resolution limits of the measuring system are exceeded. On the basis of these arguments we suggest that some classes of overturns are created with Thorpe scale larger than the Ozmidov scale. In these overturns the kinetic energy dissipation rate (e) is small during the initial growth of the overturn. Later, a small-scale structure develops, and a more complex, higher-order flow evolves. This behavior is discussed and compared with gridgenerated laboratory turbulence, in which initially small, energetic, rapidly growing boundary layers detached from the grid and advect downstream, forcing ROT to be largest adjacent to the grid and thereafter decrease as a result of entrainment.

Some statistical and dynamical properties of turbulence in the oceanic pycnocline

Statistics of turbulence length scales in individual mixing patches are used to describe the nature of mixing in the oceanic pycnocline near steep bottom topography. The majority of the observed mixing events can be explained with the conventional ideas of shear-driven turbulence. The statistics of some large patches, however, deviate substantially from expected values, suggesting that there is at least one other significant source of turbulent kinetic energy besides small-scale shear production. On the basis of inertial subrange energy arguments, it is proposed that the overturning seen in these events is a release of potential energy to kinetic energy which is consistent with advective instability in a finite-amplitude internal wave field. We find that within large turbulent patches the turbulent kinetic energy dissipation rate er averaged over a region of height r has a lognormal distribution consistent with Kolmogorovs third hypothesis, σ2ln(er) = A + μ, ln (LP/r), where σ2ln(er) is the variance of ln (er); r satisfies LP ≫ r ≫ η; LP is the size of the mixing patch; η is the Kolmogorov scale; A depends on the large-scale flow field; and μ is the intermittency coefficient, which is found to be approximately 0.4 in large patches. The variance of ln (er) also depends on the Reynolds number and the characteristic length scales of the mixing patches.

Large-Eddy Simulation of Flow over Two-Dimensional Obstacles: High Drag States and Mixing

A three-dimensional large-eddy simulation (LES) model was used to examine how stratified flow interacts with bottom obstacles in the coastal ocean. Bottom terrain representing a 2D ridge was modeled using a finitevolume approach with ridge height (4.5 m) and width (;30 m) and water depth (;45 m) appropriate for coastal regions. Temperature and salinity profiles representative of coastal conditions giving constant buoyancy frequency were applied with flow velocities between 0.16 and 0.4 m s 21. Simulations using a free-slip lower boundary yielded flow responses ranging from transition flows with relatively high internal wave pressure drag to supercritical flow with relatively small internal wave drag. Cases with high wave drag exhibited strong lee-wave systems with wavelength of ;100 m and regions of turbulent overturning. Application of bottom drag caused a 5‐10-m-thick bottom boundary layer to form, which greatly reduced the strength of lee-wave systems in the transition cases. A final simulation with bottom drag, but with a much larger obstacle height (16 m) and width (;400 m), produced a stronger lee-wave response, indicating that large obstacle flow is not influenced as much by bottom roughness. Flow characteristics for the larger obstacle were more similar to hydraulic flow, with lee waves that are relatively short in comparison with the obstacle width. The relatively strong effect of bottom roughness on the small obstacle wave drag suggests that small-scale bottom variations may be ignored in internal wave drag parameterizations. However, the more significant wave drag from larger-scale obstacles must still be considered and may be responsible for mixing and momentum transfer at distances far from the obstacle source.

Effect of surface waves on the irradiance distribution in the upper ocean

The distribution of irradiance in the upper ocean was examined from sensors mounted on an Autonomous Underwater Vehicle (AUV). Apparent and inherent optical properties along with physical variability ranging from scales O(10 cm) to O(1 km) were collected off the coast of Oregon during the summer of 2004. Horizontal wavenumber spectra of downwelling irradiance showed that irradiance varied as a function of wavenumber and depth. The analysis indicates that irradiance variability between 1 and 20 m spatial scales was attributed to the focusing effects of surface wave geometry. The dominant wavelength of focusing at depths of 2 - 6 m was about 2 m for ~6 m s-1 wind speeds.

Optical measurement of rates of dissipation of temperature variance due to oceanic turbulence

Inhomogeneities in the refractive index induced by temperature fluctuations in turbulent flows have the effect of scattering light in near-forward angles. We have developed a method that extracts the rate of Temperature Variance Dissipation (TVD) and its spectrum from the properties of light scattering and have built an instrument - Optical Turbulence Sensor (OTS) - that implements the method. OTS uses a linear wavefront sensing Hartmann array and allows for nearly instantaneous measurements of temperature variance in turbulent flows. The instrument has been tested in an situ experiment carried out from a drifting vessel at a site off the coast of Newport, Oregon. Here we compare the temperature variance measured by OTS and its spectra with both theoretical predictions and with spectra obtained from a fast thermistor sensor.