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The purpose of this study is to present the first estimates of the breaking strength parameter, b$b$ , for individual oceanic whitecaps. This is achieved by combining the estimates of the dissipation rate per unit breaking crest length for these whitecaps reported in Callaghan et al. (2024, https://doi.org/10.1029/2023jc020193) with a measure of the whitecap breaking wave speed to implement the Duncan (1981, https://doi.org/10.1098/rspa.1981.0127) relationship. The resulting values of b$b$span the range of previously reported laboratory values. Moreover, average values of b$b$are in excellent agreement with previous field‐derived average values using different approaches. The results suggest that making routine estimates of b$b$for individual whitecaps is now possible. This opens up new possibilities for how the fifth moment of Phillips' Λ(c)${\\Lambda }(c)$distribution of breaking wave crests can be better constrained to estimate the total dissipation rate of energy by oceanic whitecaps.

Drifting buoy observations of ocean surface waves in hurricanes are combined with modeled surface wind speeds. The observations include targeted aerial deployments into Hurricane Ian (2022) and opportunistic measurements from the Sofar Ocean Spotter global network in Hurricane Fiona (2022). Analysis focuses on the slope of the waves, as quantified by the spectral mean square slope. At low‐to‐moderate wind speeds (<15 m s−1), slopes increase linearly with wind speed. At higher winds (>15 m s−1), slopes continue to increase, but at a reduced rate. At extreme winds (>30 m s−1), slopes asymptote. The mean square slopes are directly related to the wave spectral shapes, which over the resolved frequency range (0.03–0.5 Hz) are characterized by an equilibrium tail (f−4${f}^{-4}$ ) at moderate winds and a saturation tail (f−5${f}^{-5}$ ) at higher winds. The asymptotic behavior of wave slope as a function of wind speed could contribute to the reduction of surface drag at high wind speeds. Plain Language Summary Drifting buoy observations of ocean surface waves in Hurricanes Ian and Fiona (2022) are combined with modeled wind speed to explore the evolution of the sea surface from moderate to extreme winds (up to 54 m s−1). The sea surface is characterized using the physical slope of the waves, or the ratio of a wave's height to its length, which has previously only been well‐understood up to moderate wind speeds of 15–20 m s−1. At lower wind speeds, the average slopes increase proportional to the wind speed, meaning the waves continually steepen as the wind strengthens. At higher winds, the slopes continue to increase, but at a reduced rate. The slopes eventually reach a maximum value at the most extreme winds (i.e., the slopes saturate). This phenomenon is accompanied by a change in sea surface character from one that is patterned by occasional wave breaking to one that is almost entirely covered by whitecaps and foam. Using wave slope as a measure of the roughness of the ocean surface, the observed wave slope saturation could help to explain the relative reduction in wind surface forcing at extreme wind speeds. Key Points Buoy observations of waves in hurricanes show the dependence of wave slope on wind speed changes above 15 m s−1 and saturates beyond 30 m s−1 Wave spectra become dominated by the saturation range at high winds suggesting wave breaking is ubiquitous and thereby limits wave slope This effect is a plausible cause for the reduction of surface drag at high wind speeds

Whitecaps are crucial for understanding ocean-atmosphere interactions, particularly under high sea states, where quantifying whitecap coverage has long been a key research focus. This study aims to validate the Whitecap Statistical Physics Model (WSPM) under high sea states using observational data. Observational data from the High Wind Speed Gas Exchange Study (HiWinGS) was used to validate the WSPM. The model's performance was assessed across multiple sites under wind speeds exceeding 15 m/s and significant wave heights (SWH) up to 10 meters. The WSPM showed good agreement with observational data at most sites, accurately capturing variations in whitecap coverage. At the same time, discrepancies in the model results were observed, which were attributed to errors in the WSPM's data sources and complex sea conditions characterized by rapid shifts in wind direction and alternating dominance of wind waves and swell. This study highlights the advantages of physics-based models over simple wind-speed-dependent parameterizations in capturing the complexities of wave dynamics. The findings suggest that the WSPM is highly effective in capturing the dynamics of whitecap coverage across a range of high sea states, providing a detailed and robust reference for its application in real-world scenarios. Further research is needed to address the sources of error and improve the model's accuracy under complex sea conditions.

Here we provide a theoretical framework revealing that the radius$R_{d}$of the top droplet ejected from a bursting bubble of radius$R_{b}$and$Bo\\leqslant 0.05$can be expressed as$R_{d}/R_{b}=K_{b}(1-(Oh/Oh_{c}^{\\prime })^{1/2})$for$Oh\\lesssim Oh_{c}^{\\prime }$or as$R_{d}\\approx 18\\,\\unicode[STIX]{x1D707}_{l}^{2}/(\\unicode[STIX]{x1D70C}_{l}\\unicode[STIX]{x1D70E})$for$Oh\\gtrsim Oh_{c}^{\\prime }$, with the numerically fitted constants$K_{b}\\approx 0.2$,$Oh_{c}^{\\prime }\\approx 0.03$,$Oh=\\unicode[STIX]{x1D707}_{l}/\\sqrt{\\unicode[STIX]{x1D70C}_{l}\\,R_{b}\\,\\unicode[STIX]{x1D70E}}\\ll 1$the Ohnesorge number,$Bo=\\unicode[STIX]{x1D70C}_{l}\\,g\\,R_{b}^{2}/\\unicode[STIX]{x1D70E}$the Bond number, and$\\unicode[STIX]{x1D70C}_{l}$,$\\unicode[STIX]{x1D707}_{l}$and$\\unicode[STIX]{x1D70E}$indicating the liquid density, dynamic viscosity and interfacial tension coefficient, respectively. These predictions, which do not only have solid theoretical roots but are also much more accurate than the usual 10 % rule used in the context of marine spray generation via whitecaps for$R_{b}\\lesssim 1$mm, agree very well with both experimental data and numerical simulations for the values of$Oh$and$Bo$investigated. Moreover, making use of a criterion which reveals the mechanism that controls the growth rate of capillary instabilities, we also explain here why no droplets are ejected from the tip of the fast Worthington jet for$Oh\\gtrsim 0.04$. In addition, our results predict the generation of submicron-sized aerosol particles with diameters below 100 nm and velocities${\\sim}\\unicode[STIX]{x1D70E}/\\unicode[STIX]{x1D707}_{l}$for bubble radii$10~\\unicode[STIX]{x03BC}\\text{m}\\lesssim R_{b}\\lesssim 20~\\unicode[STIX]{x03BC}\\text{m}$, within the range found in natural conditions and in good agreement with experiments – a fact suggesting that our study could be applied in the modelling of sea spray aerosol production.

Air‐entraining whitecaps provide an important source of bubbles over the global oceans, yet the rate at which the associated air is entrained is not well known. This lack of understanding limits the ability to accurately parameterize bubble‐mediated gas exchange and sea spray aerosol flux. In this paper I present a model to predict the total volume of air entrained by individual whitecaps and extend it to estimate the rate at which air is entrained per unit sea surface area. The model agrees well with existing models and measurements and can be forced by the rate at which energy is dissipated by the wavefield which can be routinely provided by spectral wave models. I then use the model to present the first distributions of the estimated total volume of air entrained by individual whitecaps, as well as their rate of air entrainment and air degassing. Plain Language Summary The amount of air in the oceans in the form of bubbles at any given time is not well known because of the difficulty associated with making in‐situ measurements. This lack of knowledge inhibits how well ocean‐atmosphere exchange processes that are driven by air and bubbles can be represented in climate models. In this paper, I present a new model to estimate the volume of air entrained by individual breaking waves called whitecaps, as well as how quickly the air is entrained into the oceans and how quickly it leaves the oceans when bubbles rise to the surface and burst. Key Points A model for the entrainment of air by oceanic whitecaps is presented which agrees well with existing models and measurements Distributions of the estimated volume of air entrained by individual oceanic whitecaps are presented for the first time Key uncertainties in the air fraction and entrainment velocities of individual whitecaps remain due to a lack of measurements

Field measurements of breaking waves and bubble depths were obtained using a stereo video system collocated with a submerged acoustic Doppler current profiler (ADCP) in the central North Sea. We discriminate between two bubble depths that define an active near‐surface layer and a deeper layer. The active layer intermittently sees short‐lived injected bubble depths from breakers whereas the deeper layer is dominated by persistent passive bubble plumes that remain visible for more than 50 mean wave periods. We augment traditional single‐beam bubble detection methods by utilizing all five beams of the ADCP to achieve broader spatial coverage of bubble plume measurements. The combined wave and bubble observations reveal that deep bubble plumes often occur offset spatially from surface whitecaps, suggesting that Langmuir‐type circulation plays a role in the formation and persistence of deep bubble plumes through vertical and horizontal advection.

Oceanic whitecaps are caused by wave breaking and are very important in air–sea interactions. Usually, whitecap coverage is considered a key factor in representing the role of whitecaps. However, the accurate identification of whitecap coverage in videos under dynamic marine conditions is a tough task. An EMA-SE-ResUNet deep learning model was proposed in this study to address this challenge. Based on a foundation of residual network (ResNet)-50 as the encoder and U-Net as the decoder, the model incorporated efficient multi-scale attention (EMA) module and squeeze-and-excitation network (SENet) module to improve its performance. By employing a dynamic weight allocation strategy and a channel attention mechanism, the model effectively strengthens the feature representation capability for whitecap edges while suppressing interference from wave textures and illumination noise. The model’s adaptability to complex sea surface scenarios was enhanced through the integration of data augmentation techniques and an optimized joint loss function. By applying the proposed model to a dataset collected by a shipborne camera system deployed during a comprehensive fishery resource survey in the northwest Pacific, the model results outperformed main segmentation algorithms, including U-Net, DeepLabv3+, HRNet, and PSPNet, in key metrics: whitecap intersection over union (IoUW) = 73.32%, pixel absolute error (PAE) = 0.081%, and whitecap F1-score (F1W) = 84.60. Compared to the traditional U-Net model, it achieved an absolute improvement of 2.1% in IoUW while reducing computational load (GFLOPs) by 57.3% and achieving synergistic optimization of accuracy and real-time performance. This study can provide highly reliable technical support for studies on air–sea flux quantification and marine aerosol generation.

Microwave reflectometers provide spectrally integrated information of ocean surface waves several times longer than the incident electromagnetic (EM) wavelengths. For high wind condition, it is necessary to consider the modification of relative permittivity by air in foam and whitecaps produced by wave breaking. This paper describes the application of these considerations to microwave specular returns from the ocean surface. Measurements from Ku and Ka band altimeters and L band reflectometers are used for illustration. The modeling yields a straightforward integration of a closed-form expression connecting the observed specular normalized radar cross section (NRCS) to the surface wave statistical and geometric properties. It remains a challenge to acquire sufficient number of high-wind collocated and simultaneous reference measurements for algorithm development or validation and verification effort. Solutions from accurate forward computation can supplement the sparse high wind databases. Modeled specular NRCSs are provided for L, C, X, Ku, and Ka bands with wind speeds up to 99 m/s.

We have developed an inorganic sea spray source function that is based upon state-of-the-art measurements of sea spray aerosol production using a temperature-controlled plunging jet sea spray aerosol chamber. The size-resolved particle production was measured between 0.01 and 10 μm dry diameter. Particle production decreased non-linearly with increasing seawater temperature (between −1 and 30 °C) similar to previous findings. In addition, we observed that the particle effective radius, as well as the particle surface, particle volume and particle mass, increased with increasing seawater temperature due to increased production of particles with dry diameters greater than 1 μm. By combining these measurements with the volume of air entrained by the plunging jet we have determined the size-resolved particle flux as a function of air entrainment. Through the use of existing parameterisations of air entrainment as a function of wind speed, we were subsequently able to scale our laboratory measurements of particle production to wind speed. By scaling in this way we avoid some of the difficulties associated with defining the \"white area\" of the laboratory whitecap – a contentious issue when relating laboratory measurements of particle production to oceanic whitecaps using the more frequently applied whitecap method. The here-derived inorganic sea spray source function was implemented in a Lagrangian particle dispersion model (FLEXPART – FLEXible PARTicle dispersion model). An estimated annual global flux of inorganic sea spray aerosol of 5.9 ± 0.2 Pg yr−1 was derived that is close to the median of estimates from the same model using a wide range of existing sea spray source functions. When using the source function derived here, the model also showed good skill in predicting measurements of Na+ concentration at a number of field sites further underlining the validity of our source function. In a final step, the sensitivity of a large-scale model (NorESM – the Norwegian Earth System Model) to our new source function was tested. Compared to the previously implemented parameterisation, a clear decrease of sea spray aerosol number flux and increase in aerosol residence time was observed, especially over the Southern Ocean. At the same time an increase in aerosol optical depth due to an increase in the number of particles with optically relevant sizes was found. That there were noticeable regional differences may have important implications for aerosol optical properties and number concentrations, subsequently also affecting the indirect radiative forcing by non-sea spray anthropogenic aerosols.