Distribution of breaking waves at the ocean surface

Laboratory Heat Flux Estimates of Seawater Foam for Low Wind Speeds

Laboratory experiments were conducted to measure the heat flux from seafoam continuously generated in natural seawater. Using a control volume technique, heat flux was calculated from foam and foam-free surfaces as a function of ambient humidity (ranged from 40% to 78%), air–water temperature difference (ranged from −9 °C to 0 °C), and wind speed (variable up to 3 m s−1). Water-surface skin temperature was imaged with a calibrated thermal infrared camera, and near-surface temperature profiles in the air, water, and foam were recorded. Net heat flux from foam surfaces increased with increasing wind speed and was shown to be up to four times greater than a foam-free surface. The fraction of the total heat flux due to the latent heat flux was observed for foam to be 0.75, with this value being relatively constant with wind speed. In contrast, for a foam-free surface the fraction of the total heat flux due to the latent heat flux decreased at higher wind speeds. Temperature profiles through foam are linear and have larger gradients, which increased with wind speed, while foam free surfaces show the expected logarithmic profile and show no variation with temperature. The radiometric surface temperatures show that foam is cooler and more variable than a foam-free surface, and bubble-resolving thermal images show that radiometrically transparent bubble caps and burst bubbles reveal warm foam below the cool surface layer, contributing to the enhanced variability.

Sea spray aerosol concentration modulated by sea surface temperature

Climate models use pre-industrial atmosphere as the reference to evaluate the impacts of human activities on the Earth’s radiation balance. Sea spray aerosols (SSA) are the key component in the relatively pristine preindustrial conditions that substantially affect model calculations. Currently, the abundance of SSA is poorly constrained. In particular, studies on the influence of sea surface temperature on SSA production have shown disparate results. This uncertainty arises from limited field measurements, especially over remote oceans. Our global aircraft measurements over the remote Pacific and Atlantic Oceans show that higher sea surface temperature enhances the production of SSA. Updating the current parameterization in global models using our observational constraints will improve the estimate of atmospheric SSA budget and human-induced climate change.

Natural aerosols in pristine regions form the baseline used to evaluate the impact of anthropogenic aerosols on climate. Sea spray aerosol (SSA) is a major component of natural aerosols. Despite its importance, the abundance of SSA is poorly constrained. It is generally accepted that wind-driven wave breaking is the principle governing SSA production. This mechanism alone, however, is insufficient to explain the variability of SSA concentration at given wind speed. The role of other parameters, such as sea surface temperature (SST), remains controversial. Here, we show that higher SST promotes SSA mass generation at a wide range of wind speed levels over the remote Pacific and Atlantic Oceans, in addition to demonstrating the wind-driven SSA production mechanism. The results are from a global scale dataset of airborne SSA measurements at 150 to 200 m above the ocean surface during the NASA Atmospheric Tomography Mission. Statistical analysis suggests that accounting for SST greatly enhances the predictability of the observed SSA concentration compared to using wind speed alone. Our results support implementing SST into SSA source functions in global models to better understand the atmospheric burdens of SSA.

Deep neural networks for active wave breaking classification

Wave breaking is an important process for energy dissipation in the open ocean and coastal seas. It drives beach morphodynamics, controls air-sea interactions, determines when ship and offshore structure operations can occur safely, and influences on the retrieval of ocean properties from satellites. Still, wave breaking lacks a proper physical understanding mainly due to scarce observational field data. Consequently, new methods and data are required to improve our current understanding of this process. In this paper we present a novel machine learning method to detect active wave breaking, that is, waves that are actively generating visible bubble entrainment in video imagery data. The present method is based on classical machine learning and deep learning techniques and is made freely available to the community alongside this publication. The results indicate that our best performing model had a balanced classification accuracy score of [Formula: see text] 90% when classifying active wave breaking in the test dataset. An example of a direct application of the method includes a statistical description of geometrical and kinematic properties of breaking waves. We expect that the present method and the associated dataset will be crucial for future research related to wave breaking in several areas of research, which include but are not limited to: improving operational forecast models, developing risk assessment and coastal management tools, and refining the retrieval of remotely sensed ocean properties.

Hybrid Triboelectric Nanogenerators: From Energy Complementation to Integration

Energy collection ways using solar energy, wave, wind, or mechanical energy have attracted widespread attention for small self-powered electronic devices with low power consumption, such as sensors, wearable devices, electronic skin, and implantable devices. Among them, triboelectric nanogenerator (TENG) operated by coupling effect of triboelectrification and electrostatic induction has gradually gained prominence due to its advantages such as low cost, lightweight, high degree of freedom in material selection, large power, and high applicability. The device with a single energy exchange mechanism is limited by its conversion efficiency and work environment and cannot achieve the maximum conversion of energy. Thus, this article reviews the research status of different types of hybrid generators based on TENG in recent years. Hybrid energy generators will improve the output performance though the integration of different energy exchange methods, which have an excellent application prospect. From the perspective of energy complementation, it can be divided into harvesting mechanical energy by various principles, combining with harvesters of other clean energy, and converting mechanical energy or various energy sources into hydrogen energy. For integrating multitype energy harvesters, mechanism of single device and structural design of integrated units for different application scenarios are summarized. The expanding energy harvesting efficiency of the hybrid TENG makes the scheme of self-charging unit to power intelligent mobile electronic feasible and has practical significance for the development of self-powered sensor network.

Estimating Energy Dissipation Rate from Breaking Waves Using Polarimetric SAR Images

The total energy dissipation rate on the ocean surface, ϵt (W m−2), provides a first-order estimation of the kinetic energy input rate at the ocean–atmosphere interface. Studies on the spatial and temporal distribution of the energy dissipation rate are important for the improvement of climate and wave models. Traditional oceanographic research normally uses remote measurements (airborne and platforms sensors) and in situ data acquisition to estimate ϵt; however, those methods cover small areas over time and are difficult to reproduce especially in the open oceans. Satellite remote sensing has proven the potential to estimate some parameters related to breaking waves on a synoptic scale, including the energy dissipation rate. In this paper, we use polarimetric Synthetic Aperture Radar (SAR) data to estimate ϵt under different wind and sea conditions. The used methodology consisted of decomposing the backscatter SAR return in terms of two contributions: a polarized contribution, associated with the fast response of the local wind (Bragg backscattering), and a non-polarized (NP) contribution, associated with wave breaking (Non-Bragg backscattering). Wind and wave parameters were estimated from the NP contribution and used to calculate ϵt from a parametric model dependent of these parameters. The results were analyzed using wave model outputs (WAVEWATCH III) and previous measurements documented in the literature. For the prevailing wind seas conditions, the ϵt estimated from pol-SAR data showed good agreement with dissipation associated with breaking waves when compared to numerical simulations. Under prevailing swell conditions, the total energy dissipation rate was higher than expected. The methodology adopted proved to be satisfactory to estimate the total energy dissipation rate for light to moderate wind conditions (winds below 10 m s−1), an environmental condition for which the current SAR polarimetric methods do not estimate ϵt properly.

Extracting the surface tension of soft gels from elastocapillary wave behavior

Mechanically-excited waves appear as surface patterns on soft agarose gels. We experimentally quantify the dispersion relationship for these waves over a range of shear modulus in the transition zone where the surface energy (capillarity) is comparable to the elastic energy of the solid. Rayleigh waves and capillary-gravity waves are recovered as limiting cases. Gravitational forces appear as a pre-stress through the self-weight of the gel and are important. We show the experimental data fits well to a proposed dispersion relationship which differs from that typically used in studies of capillary to elastic wave crossover. We use this combined theoretical and experimental analysis to develop a new technique for measuring the surface tension of soft materials, which has been historically difficult to measure directly.

Direct numerical simulations of capillary wave turbulence

This work presents direct numerical simulations of capillary wave turbulence solving the full three-dimensional Navier-Stokes equations of a two-phase flow. When the interface is locally forced at large scales, a statistical stationary state appears after few forcing periods. Smaller wave scales are generated by nonlinear interactions, and the wave height spectrum is found to obey a power law in both wave number and frequency, in good agreement with weak turbulence theory. By estimation of the mean energy flux from the dissipated power, the Kolmogorov-Zakharov constant is evaluated and found to be compatible with the exact theoretical value. The time scale separation between linear, nonlinear interaction, and dissipative times is also observed. These numerical results confirm the validity of the weak turbulence approach to quantify out-of equilibrium wave statistics.

Lagrangian-Eulerian dynamics of breaking shallow water waves through tracer tracking of fluid elements

We experimentally investigate the Lagrangian-Eulerian dynamics of fluid motion and wave-form evolution for a breaking shallow water wave approaching a slope by tracking tracer motions. It is found that, before breaking, the surface element can climb over the crest and exhibits cyclic oscillation with small forward drift. The increasing asymmetric tangential compression (accumulation) and rarefaction (depletion) in the crest front and the crest are the keys for the crest front steepening with the increasing particle cyclic excursion and forward Stoke drift. Eventually, the surface layer cannot climb over the crest with the vertical front. It curls up and forms an overhanging plunging jet leading the crest, while the lower flow still can reach the crest rear. This process leads to wave breaking with the rapid drop of crest height and the transition from slow divergence to rapid divergence of the adjacent fluid trajectories.

Bottom profiling by correlating beam-steered noise sequences

It has already been established that by cross-correlating ambient noise time series received on the upward and downward steered beams of a drifting vertical array one can obtain a subbottom layer profile. Strictly, the time differential of the cross correlation is the impulse response of the seabed. Here it is shown theoretically and by simulation that completely uncorrelated surface noise results in a layer profile with predictable amplitudes proportional to those of an equivalent echo sounder at the same depth as the array. The phenomenon is simulated by representing the sound sources as multiple random time sequences emitted from random locations in a horizontal plane above a vertical array and then accounting for the travel times of the direct and bottom reflected paths. A well-defined correlation spike is seen at the depth corresponding to the bottom reflection despite the fact that the sound sources contain no structure whatsoever. The effects of using simultaneously steered upward and downward conical beams with a tilted or faceted seabed and multiple layers are also investigated by simulation. Experimental profiles are obtained using two different vertical arrays in smooth and rough bottom sites in the Mediterranean. Correlation peak amplitudes follow the theory and simulations closely.