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The particle trajectories in irrotational, incompressible and inviscid deep-water surface gravity waves are open, leading to a net drift in the direction of wave propagation commonly referred to as the Stokes drift, which is responsible for catalysing surface wave-induced mixing in the ocean and transporting marine debris. A balance between phase-averaged momentum density, kinetic energy density and vorticity for irrotational, monochromatic and spatially periodic two-dimensional water waves is derived by working directly within the Lagrangian reference frame, which tracks particle trajectories as a function of their labels and time. This balance should be expected as all three of these quantities are conserved following particles in this system. Vorticity in particular is always conserved along particles in two-dimensional inviscid flow, and as such even in its absence it is the value of the vorticity that fundamentally sets the drift, which in the Lagrangian frame is identified as the phase-averaged momentum density of the system. A relationship between the drift and the geometric mean water level of particles is found at the surface, which highlights connections between the geometry and dynamics. Finally, an example of an initially quiescent fluid driven by a wavelike pressure disturbance is considered, showing how the net momentum and energy from the surface pressure disturbance transfer to the wave field, and recognizing the source of the mean Lagrangian drift as the net momentum required to generate an irrotational surface wave by any conservative force. 

A light breeze rising over calm water initiates an intricate chain of events that culminates in a centimetres-deep turbulent shear layer capped by gravity–capillary ripples. At first, viscous stress accelerates a laminar wind-drift layer until small surface ripples appear. The surface ripples then catalyse the growth of a second instability in the wind-drift layer, which eventually sharpens into along-wind jets and downwelling plumes, before devolving into three-dimensional turbulence. In this paper, we compare laboratory experiments with simplified, wave-averaged numerical simulations of wind-drift layer evolution beneath monochromatic, constant-amplitude surface ripples seeded with random initial perturbations. Despite their simplicity, our simulations reproduce many aspects of the laboratory-based observations – including the growth, nonlinear development and turbulent breakdown the wave-catalysed instability – generally validating our wave-averaged model. But we also find that the simulated development of the wind-drift layer is disturbingly sensitive to the amplitude of the prescribed surface wave field, such that agreement is achieved through suspiciously careful tuning of the ripple amplitude. As a result of this sensitivity, we conclude that wave-averaged models should really describe the coupled evolution of the surface waves together with the flow beneath to be regarded as truly ‘predictive’. 

The role of the Lagrangian mean flow, or drift, in modulating the geometry, kinematics and dynamics of rotational and irrotational deep-water surface gravity waves is examined. A general theory for permanent progressive waves on an arbitrary vertically sheared steady Lagrangian mean flow is derived in the Lagrangian reference frame and mapped to the Eulerian frame. A Lagrangian viewpoint offers tremendous flexibility due to the particle labelling freedom and allows us to reveal how key physical wave behaviour arises from a kinematic constraint on the vorticity of the fluid, inter alia the nonlinear correction to the phase speed of irrotational finite amplitude waves, the free surface geometry and velocity in the Eulerian frame, and the connection between the Lagrangian drift and the Benjamin–Feir instability. To complement and illustrate our theory, a small laboratory experiment demonstrates how a specially tailored sheared mean flow can almost completely attenuate the Benjamin–Feir instability, in qualitative agreement with the theory. The application of these results to problems in remote sensing and ocean wave modelling is discussed. We provide an answer to a long-standing question: remote sensing techniques based on observing current-induced shifts in the wave dispersion will measure the Lagrangian, not the Eulerian, mean current. 

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. 

While it has long been recognized that Lagrangian drift at the ocean surface plays a critical role in the kinematics and dynamics of upper ocean processes, only recently has the contribution of wave breaking to this drift begun to be investigated through direct numerical simulations (Deike et al. ,  J. Fluid Mech. , vol. 829, 2017, pp. 364–391; Pizzo et al. ,  J. Phys. Oceanogr. , vol. 49(4), 2019, pp. 983–992). In this work, laboratory measurements of the surface Lagrangian transport due to focusing deep-water non-breaking and breaking waves are presented. It is found that wave breaking greatly enhances mass transport, compared to non-breaking focusing wave packets. These results are in agreement with the direct numerical simulations of Deike  et al. ( J. Fluid Mech. , vol. 829, 2017, pp. 364–391), and the increased transport due to breaking agrees with their scaling argument. In particular, the transport at the surface scales with $$S$$ , the linear prediction of the maximum slope at focusing, while the surface transport due to non-breaking waves scales with $$S^{2}$$ , in agreement with the classical Stokes prediction. 

As reported in 1954, more than a half century ago, C. Cox and W. Munk developed an empirical model of the slope distribution of ocean surface waves that has been widely used ever since to model the optical properties of the sea surface and is of particular importance to the satellite remote sensing community. In that work, the reflectance of sunlight was photographed from a Boeing B-17G bomber and was then analyzed. In this paper, surface slope statistics are investigated from airborne scanning topographic lidar data collected during a series of field experiments off the coast of California and in the Gulf of Mexico, over a broad range of environmental conditions, with wind speeds ranging from approximately 2 to 13 m s −1 . Unlike the reflectance-based approach of Cox and Munk, the slope distribution is computed by counting laser glints produced by specular reflections as the lidar is scanned over the surface of the ocean. We find good agreement with their measurements for the mean-square slope and with more recent (2006) results from Bréon and Henriot that were based on satellite remote sensing. Significant discrepancies for the higher-order statistics are found and discussed. We also demonstrate here that airborne scanning lidar technology offers a viable means of remotely estimating surface wind speed and momentum flux. 

An analysis of coherent measurements of winds and waves from data collected during the ONR Southern California 2013 (SoCal2013) program from R/P FLIP off the coast of Southern California in November 2013 is presented. An array of ultrasonic anemometers mounted on a telescopic mast was deployed to resolve the vertical profile of the modulation of the marine atmospheric boundary layer by the waves. Spectral analysis of the data provides the wave-induced components of the wind velocity for various wind-wave conditions. Results show that the wave-induced fluctuations depend both on the spectral wave age [Formula: see text] and the normalized height [Formula: see text], where c is the linear phase speed of the waves with wavenumber k and [Formula: see text] is the mean wind speed measured at the height z. The dependence on the spectral wave age expresses the sensitivity of the wave-induced airflow to the critical layer where [Formula: see text]. Across the critical layer, there is a significant change of both the amplitude and phase of the wave-induced fluctuations. Below the critical layer, the phase remains constant while the amplitude decays exponentially depending on the normalized height. Accounting for this double dependency, the nondimensionalization of the amplitude of the wave-induced fluctuations by the surface orbital velocity [Formula: see text] collapses all the data measured by the array of sonic anemometers, where a is the amplitude of the waves.