Observations of turbulent kinetic energy (TKE) dynamics in the ocean surface boundary layer are presented here and compared with results from previous observational, numerical, and analytic studies. As in previous studies, the dissipation rate of TKE is found to be higher in the wavy ocean surface boundary layer than it would be in a flow past a rigid boundary with similar stress and buoyancy forcing. Estimates of the terms in the turbulent kinetic energy equation indicate that, unlike in a flow past a rigid boundary, the dissipation rates cannot be balanced by local production terms, suggesting that the transport of TKE is important in the ocean surface boundary layer. A simple analytic model containing parameterizations of production, dissipation, and transport reproduces key features of the vertical profile of TKE, including enhancement near the surface. The effective turbulent diffusion coefficient for heat is larger than would be expected in a rigid-boundary boundary layer. This diffusion coefficient is predicted reasonably well by a model that contains the effects of shear production, buoyancy forcing, and transport of TKE (thought to be related to wave breaking). Neglect of buoyancy forcing or wave breaking in the parameterization results in poor predictions of turbulent diffusivity. Langmuir turbulence was detected concurrently with a fraction of the turbulence quantities reported here, but these times did not stand out as having significant differences from observations when Langmuir turbulence was not detected.

Recently, the velocity observations of acoustic Doppler current profilers (ADCPs) have been successfully used to estimate turbulent Reynolds stresses in estuaries and tidal channels. However, the presence of surface gravity waves can significantly bias stress estimates, limiting application of the technique in the coastal ocean. This work describes a new approach to estimate Reynolds stresses from ADCP velocities obtained in the presence of waves. The method fits an established semiempirical model of boundary layer turbulence to the measured turbulent cospectra at frequencies below those of surface gravity waves to estimate the stress. Applied to ADCP observations made in weakly stratified waters and variable significant wave heights, estimated near-bottom and near-surface stresses using this method compared well with independent estimates of the boundary stresses in contrast to previous methods. Additionally, the vertical structure of tidal stress estimated using the new approach matched that inferred from a linear momentum balance at stress levels below the estimated stress uncertainties. Because the method makes an estimate of the horizontal turbulent length scales present as part of the model fit, these results can also enable a direct correction for the mean bias errors resulting from instrument tilt, if these scales are long relative to the beam separation.

This study makes direct measurements of turbulent fluxes in the mixed layer in order to close heat and momentum budgets across the air-sea interface and to assess the ability of rigid-boundary turbulence models to predict mean vertical gradients beneath the ocean's wavy surface. Observations were made at 20 Hz at nominal depths of 2.2 and 1.7 m in ϳ16 m of water. A new method is developed to estimate the fluxes and the length scales of dominant flux-carrying eddies from cospectra at frequencies below the wave band. The results are compared to independent estimates of those quantities, with good agreement between the two sets of estimates. The observed temperature gradients were smaller than predicted by standard rigidboundary closure models, consistent with the suggestion that wave breaking and Langmuir circulation increase turbulent diffusivity in the upper ocean. Similarly, the Monin-Obukhov stability function h was smaller in the authors' measurements than the stability functions used in rigid-boundary applications of the Monin-Obukhov similarity theory. The dominant horizontal length scales of flux-carrying turbulent eddies were found to be consistent with observations in the bottom boundary layer of the atmosphere and from laboratory experiments in three ways: 1) in statically unstable conditions, the eddy sizes scaled linearly with distance to the boundary; 2) in statically stable conditions, length scales decreased with increasing downward buoyancy flux; and 3) downwind length scales were larger than crosswind length scales.

Hydrodynamic signals from turbulence and waves may provide marine invertebrate larvae with behavioral cues that affect the pathways and energetic costs of larval delivery to adult habitats. Oysters (Crassostrea virginica) live in sheltered estuaries with strong turbulence and small waves, but their larvae can be transported into coastal waters with large waves. These contrasting environments have different ranges of hydrodynamic signals, because turbulence generally produces higher spatial velocity gradients, whereas waves can produce higher temporal velocity gradients. To understand how physical processes affect oyster larval behavior, transport and energetics, we exposed larvae to different combinations of turbulence and waves in flow tanks with (1) wavy turbulence, (2) a seiche and (3) rectilinear accelerations. We quantified behavioral responses of individual larvae to local instantaneous flows using twophase, infrared particle-image velocimetry. Both high dissipation rates and high wave-generated accelerations induced most larvae to swim faster upward. High dissipation rates also induced some rapid, active dives, whereas high accelerations induced only weak active dives. In both turbulence and waves, faster swimming and active diving were achieved through an increase in propulsive force and power output that would carry a high energetic cost. Swimming costs could be offset if larvae reaching surface waters had a higher probability of being transported shoreward by Stokes drift, whereas diving costs could be offset by enhanced settlement or predator avoidance. These complex behaviors suggest that larvae integrate multiple hydrodynamic signals to manage dispersal tradeoffs, spending more energy to raise the probability of successful transport to suitable locations.