Mika Petteri Malila

Langmuir turbulence is a key mechanism to enhanced mixing in the upper ocean. Although often associated with wind, the theoretical framework proposed by Craik and Leibovich requires only vorticity and wave‐induced Stokes drift, regardless of their cause. In a laboratory flume, we make waves of varying steepness interact with a turbulent current to measure the vertical transport of a passive scalar directly. Once waves appear, the turbulent flow changes radically with long, intense Langmuir (like) vortices forming near the surface, aligned with the wave direction. Combining stereo particle‐image velocimetry and laser‐induced fluorescence, we simultaneously measure the turbulent velocity field and the concentration field of a surface‐injected dye, showing dramatic enhancement and deepening of the vertical scalar flux, increasing with wave steepness. The Langmuir enhancement factor for mixing is measured in the range 4–6. The results are consistent with three different variants of the most‐used parameterization of oceanic wave‐induced mixing.

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.

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.

We examine the dependence of the penetration depth and fractional surface area (e.g., whitecap coverage) of bubble plumes generated by breaking surface waves on various wind and wave parameters over a wide range of sea state conditions in the North Pacific Ocean, including storms with sustained winds up to 22 m s⁻¹ and significant wave heights up to 10 m. Our observations include arrays of freely drifting SWIFT buoys together with shipboard systems, which enabled concurrent high‐resolution measurements of wind, waves, bubble plumes, and turbulence. We estimate bubble plume penetration depth from echograms extending to depths of more than 30 m in a surface‐following reference frame collected by downward‐looking echosounders integrated onboard the buoys. Our observations indicate that mean and maximum bubble plume penetration depths exceed 10 and 30 m beneath the surface during high winds, respectively, with plume residence times of many wave periods. They also establish strong correlations between bubble plume depths and wind speeds, spectral wave steepness, and whitecap coverage. Interestingly, we observe a robust linear correlation between plume depths, when scaled by the total significant wave height, and the inverse of wave age. However, scaled plume depths exhibit non‐monotonic variations with increasing wind speeds. Additionally, we explore the dependencies of the combined observations on various non‐dimensional predictors used for whitecap coverage estimation. This study provides the first field evidence of a direct relation between bubble plume penetration depth and whitecap coverage, suggesting that the volume of bubble plumes could be estimated by remote sensing.

We examine the dependence of the penetration depth and fractional surface area (e.g., whitecap coverage) of bubble plumes generated by breaking surface waves on various wind and wave parameters over a wide range of sea state conditions in the North Pacific Ocean, including storms with sustained winds up to 22 ms$^{-1}$ and significant wave heights up to 10 m. Observations include arrays of freely drifting SWIFT buoys together with shipboard wind and optical video systems, which enabled concurrent high-resolution measurements of wind, waves, bubble plumes, and turbulence. We estimate bubble plume penetration depth from echograms that extend to more than 30 m depth in a surface-following reference frame collected by downward-looking echosounders integrated onboard the buoys. Our observations indicate that the mean and maximum bubble plume penetration depths exceed 10 m and 30 m beneath the surface at high winds, respectively, with a plume residence time of many wave periods. Bubble plume depths are well correlated with wind speeds, spectral wave steepness, and whitecap coverage. Plume depths scaled by total significant wave height are strongly linearly correlated with the inverse of wave age. Plume depths scaled by either wind sea or total significant wave height vary non-monotonically with increasing wind speeds. Dependencies of the combined observations on various non-dimensional predictors used for whitecap coverage estimation are also explored. This study provides first field evidence of a direct relation between bubble plume penetration depth and whitecap coverage, suggesting that the volume of bubble plumes could be estimated by remote sensing.

Wave crests of unexpected height and steepness pose a danger to activities at sea, and long-term field measurements provide important clues for understanding the environmental conditions that are conducive to their generation and behavior. We present a novel dataset of high-frequency laser altimeter measurements of the sea surface elevation gathered over a period of 18 years from 2003 to 2020 on an offshore platform in the central North Sea. Our analysis of crest height distributions in the dataset shows that mature, high sea states with high spectral steepness and narrow directional spreading exhibit crest height statistics that significantly deviate from standard second-order models. Conversely, crest heights in developing sea states with similarly high steepness but wide directional spread correspond well to second-order theory adjusted for broad frequency bandwidth. The long-term point time series measurements are complemented with space–time stereo video observations from the same location, collected during five separate storm events during the 2019/20 winter season. An examination of the crest dynamics of the space–time extreme wave crests in the stereo video dataset reveals that the crest speeds exhibit a slowdown localized around the moment of maximum crest elevation, in line with prevailing theory on nonlinear wave group dynamics. Extending on previously published observations focused on breaking crests, our results are consistent for both breaking and nonbreaking extreme crests. We show that wave crest steepness estimated from time series using the linear dispersion relation may overestimate the geometrically measured crest steepness by up to 25% if the crest speed slowdown is not taken into account. Significance Statement: Better understanding of the statistics and dynamical behavior of extreme ocean surface wave crests is crucial for improving the safety of various operations at sea. Our study provides new, long-term field evidence of the combined effects of wave field steepness and directionality on the statistical distributions of crest heights in storm conditions. Moreover, we show that the dynamical characteristics of extreme wave crests are well described by recently identified nonlinear wave group dynamics. This finding has implications, for example, for wave force calculations and the treatment of wave breaking in numerical wave models.

The enhancement of wave breaking activity during wave group passage is investigated using coherent field observations of the instantaneous sea surface elevation and whitecap coverage from platform‐based stereo video measurements in the central North Sea. Passing wave groups are shown to be associated with a two to threefold enhancement in the probability distribution of total whitecap coverage W whereas the enhancement of active whitecap coverage W_A is approximately fivefold. Breaking time scales and intermittency characteristics are also investigated with the inclusion of a secondary data set of W and W_A observations collected during a research cruise in the North Pacific. The time scale analysis suggests a universal periodicity in wave breaking activity within a representative sea‐surface area encompassing approximately one dominant wave crest. The breaking periodicity is shown to be closely linked to the peak period of the dominant wave components, suggesting that long‐wave modulation of wave breaking is a predominant mechanism controlling the intermittency of wave breaking across scales.

We propose a methodology for despiking ocean surface wave time series based on a Bayesian approach to data-driven learning known as Gaussian process (GP) regression. We show that GP regression can be used for both robust detection of erroneous measurements and interpolation over missing values, while also obtaining a measure of the uncertainty associated with these operations. In comparison with a recent dynamical phase space–based despiking method, our data-driven approach is here shown to lead to improved wave signal correlation and spectral tail consistency, although at a significant increase in computational cost. Our results suggest that GP regression is thus especially suited for offline quality control requiring robust noise detection and replacement, where the subsequent analysis of the despiked data is sensitive to the accidental removal of extreme or rare events such as abnormal or rogue waves. We assess our methodology on measurements from an array of four collocated 5-Hz laser altimeters during a much-studied storm event in the North Sea covering a wide range of sea states.

Alaskan Arctic coastlines are protected seasonally from ocean waves by the presence of coastal and shorefast sea ice. This study presents field observations collected during the autumn 2019 freeze up near Icy Cape, a coastal headland in the Chukchi Sea of the Western Arctic. The evolution of the coupled air‐ice‐ocean‐wave system during a 4‐day wave event was monitored using drifting wave buoys, a cross‐shore mooring array, and ship‐based measurements. The incident wavefield with peak period of 2.5 s was attenuated by coastal pancake and frazil sea ice, reducing significant wave height by 40% over less than 5 km of cross‐shelf distance spanning water depths from 13 to 30 m. Spectral attenuation coefficients are evaluated with respect to wave and ice conditions and the proximity to the ice edge. Attenuation rates are found to be three times higher within 500 m of the ice edge, relative to values farther in the ice cover. Attenuation coefficients are in the range of 〈2.3, 2.7〉x10^‐3 m⁻¹, and follow a power‐law dependence on frequency.