This paper is the first of a two part series that investigates passive buoyant tracers in the ocean surface boundary layer. The first part examines the influence of equilibrium wind-waves on vertical tracer distributions, based on large eddy simulations (LES) of the wave-averaged Navier-Stokes equation. The second part applies the model to investigate observations of buoyant microplastic marine debris, which has emerged as a major ocean pollutant. The LES model captures both Langmuir turbulence (LT) and enhanced turbulent kinetic energy input due to breaking waves (BW) by imposing equilibrium wind-wave statistics for a range of wind and wave conditions. Concentration profiles of LES agree well with analytic solutions obtained for an eddy diffusivity profile that is constant near the surface and transitions into the K-Profile Parameterization (KPP) profile shape at greater depth. For a range of wind and wave conditions, the eddy diffusivity normalized by the product of water-side friction velocity and mixed layer depth, h, mainly depends on a single nondimensional parameter, the peak wavelength (which is related to Stokes drift decay depth) normalized by h. For smaller wave ages, BW critically enhances near-surface mixing, while LT effects are relatively small. For greater wave ages, both BW and LT contribute to elevated near-surface mixing, and LT significantly increases turbulent transport at greater depth. We identify a range of realistic wind and wave conditions for which only Langmuir (and not BW or shear driven) turbulence is capable of deeply submerging buoyant tracers.

This paper is the second of a two‐part series that investigates passive buoyant tracers in the ocean surface boundary layer (OSBL). The first part examines the influence of equilibrium wind‐waves on vertical tracer distributions, based on large eddy simulations (LESs) of the wave‐averaged Navier‐Stokes equation. Motivated by observations of buoyant microplastic marine debris (MPMD), this study applies the LES model and the parametric one‐dimensional column model from part one to examine the vertical distributions of MPMD. MPMD is widely distributed in vast regions of the subtropical gyres and has emerged as a major open ocean pollutant whose distribution is subject to upper ocean turbulence. The models capture shear‐driven turbulence, Langmuir turbulence (LT), and enhanced turbulent kinetic energy input due to breaking waves (BWs). Model results are only consistent with observations of MPMD profiles and the relationship between surface concentrations and wind speed if LT effects are included. Neither BW nor shear‐driven turbulence is capable of deeply submerging MPMD, suggesting that the observed vertical MPMD distributions are a characteristic signature of wave‐driven LT. Thus, this study demonstrates that LT substantially increases turbulent transport in the OSBL, resulting in deep submergence of buoyant tracers. The parametric model is applied to 11 years of observations in the North Atlantic and North Pacific subtropical gyres to show that surface measurements substantially underestimate MPMD concentrations by a factor of 3–13.

Since the 1970s, analytical models of coastal trapped waves (CTWs) have been developed using a first-order wave equation in the long-wave limit. Formulations of this kind require assumptions of a straight coastline with similar shelf bathymetry. These assumptions prevent the models from capturing the scattering and backscattering behavior of propagating CTWs that encounter changing coastlines, bathymetry, or shelf width. CTW modes from two different analytical models, one of which includes friction and stratification, are compared with CTW observations of velocity and pressure from a study region near the Outer Banks off the North Carolina coast in the United States. The coastline in the study region is relatively straight locally but is bounded by an estuary to the north and shelf narrowing to the south, both of which induce scattering. The models suggest that the CTWs in this region are insensitive to changes in stratification, implying that observed seasonal differences in wave magnitude are due to seasonal wind forcing. Furthermore, friction is found to be important, particularly for mode-1 propagation, but higher-order modes are prevalent despite the importance of friction. There is very poor agreement between the observed and modeled free and forced CTWs because of scattering. This lack of agreement indicates that this is not a globally applicable theoretical formulation because many global coastlines violate the basic assumptions.

Many activities require accurate wind and wave forecasts in the coastal ocean. The assimilation of fixed buoy observations into spectral wave models such as SWAN (Simulating Waves Nearshore) can provide improved estimates of wave forecasts fields. High-frequency (HF) radar observations provide a spatially expansive dataset in the coastal ocean for assimilation into wave models. A forward model for the HF Doppler spectrum based on first- and second-order Bragg scattering was developed to assimilate the HF radar wave observations into SWAN. This model uses the spatially varying wave spectra computed using the SWAN model, forecast currents from the Navy Coastal Ocean Model (NCOM), and system parameters from the HF radar sites to predict time-varying range-Doppler maps. Using an adjoint of the HF radar model, the error between these predictions and the corresponding HF Doppler spectrum observations can be translated into effective wave-spectrum errors for assimilation in the SWAN model for use in correcting the wind forcing in SWAN. The initial testing and validation of this system have been conducted using data from ten HF radar sites along the Southern California Bight during the CASPER-West experiment in October 2017. The improved winds compare positively to independent observation data, demonstrating that this algorithm can be utilized to fill an observational gap in the coastal ocean for winds and waves.