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.

Data captured by a Synthetic Aperture Sonar (SAS) near Mobile Bay during the 2021 Undersea Remote Sensing experiment funded by the Office of Naval Research reveals near surface bubble clouds from wave breaking events and a large aggregation of fish. Tools developed for using SAS data to image hydrodynamic features in the water column were applied to observations of the bubble clouds and fish aggregation. Combining imagery and height data captured by the sonar array with a detection and tracking algorithm enables the trajectories, velocities, and behavior of fish in the aggregation to be observed. Fitting the velocity and height data of the tracked objects to a Gaussian mixture model and performing cluster analysis enables an estimate of the near-surface ambient velocity via observation of the movement of the bubble traces and the general direction of motion of the fish aggregation. We find that the velocity traces associated with bubbles are consistent with ambient currents as opposed to the direction of propagating wave crests while velocities of fish indicate relatively large, pelagic species.

Tidal intrusion fronts are surface convergences that occur at constrictions in estuaries during the flood tide, separating incoming higher-salinity water from lower-salinity, stratified estuarine water. Previous observations of tidal intrusion fronts describe a V-shaped planform, with the apex of the V pointing into the estuary, however the significance of this structure has not been previously explained. Observations near the mouth of the James River estuary during the flood tide reveal the development of a quasi-steady, V-shaped front. Considering a reference frame oriented normal to the front, the velocity and density structure are consistent with gravity-current dynamics, but the oblique orientation of the front relative to the impinging flow indicates strong, along-front shear, which results from vorticity produced by flow separation at the lateral boundaries as well as topographic torque from upstream. The combination of convergence and along-front shear leads to enhanced mixing, as revealed by acoustic backscatter images of shear instability and persistent subcritical gradient Richardson number in the frontal zone. Oblique fronts such as this tidal intrusion front are common features of estuaries, and they play an important role in vertical exchange due to subduction and mixing of surface water.

The five-beam Nortek Signature series acoustic Doppler current profilers (ADCPs) include a vertical beam that can be operated as an echosounder. These echosounders record an echo intensity level as a function of range in hundredths of a decibel. While these recorded levels provide valuable qualitative information about scattering from the water column, without calibration the units’ recorded echo intensities cannot be linked quantitatively to scattering processes. In this report we summarize calibration results for six Nortek Signature1000 units. The echosounders were calibrated in the field while deployed on 4th generation Surface Wave Instrument Floats with Tracking (SWIFTs) by suspending 38.1-mm tungsten carbide spheres with 6% cobalt binder below. Here, we summarize the equations used to process Nortek Signature series echosounder data, general calibration procedures for echosounders, the methodology used to calibrate the six units, the results of the calibrations, and uncertainties and recommendations for future work. In addition, we present post-processed, calibrated echosounder data from a deployment of the SWIFTs equipped with the Signature1000s in Mobile Bay, Alabama.

When we hear about offshore energy in the news media and other popular information sources, images of oil platforms and, more recently, wind farms flash across our screens. However, there is a new, rarely known sector of offshore energy under development that is focused on harnessing the renewable power contained in ocean waves and currents and converting it to electricity. These new technologies termed marine energy converters (MECs) are the topic of this article. They not only have the potential to make a significant contribution to our energy needs but may also generate new sources of anthropogenic sounds in the oceans that require measurement and characterization to ensure that there are no harmful effects to marine life.

Strong spatial gradients and rapidly evolving, three-dimensional structure make estuarine fronts difficult to sample. Echosounders can be used near fronts to provide nearly synoptic images of water column processes and, with sufficient bandwidth, can provide quantitative information about dynamical variables derived from forward and inverse methods using acoustic backscattering measurements. This manuscript discusses measurements using broadband (50-420 kHz) echosounders from the James River (Virginia, USA) tidal intrusion front. The dominant backscattering mechanisms observed at the site include bubbles, turbulent microstructure, interfaces associated with stratification, suspended sediment, and biota. Existing analytical models are used to interpret contributions from these sources with acoustic inversions providing quantitative information about the physical structure and processes that compare favorably with conventional, in situ measurements. Supporting data sets for this analysis include measurements of temperature, salinity, velocity, and turbidity; X-band radar images of sea surface roughness; aerial optical imagery; Lagrangian measurements of waves, turbulence, and velocity structure; and Regional Ocean Modeling System circulation model simulations. A notable advantage of acoustic remote sensing is the ability to resolve processes at considerably higher spatial resolution (< 1 m horizontal; < 5 cm vertical) than other in situ sampling approaches.

Synthetic aperture sonar (SAS) systems are designed to observe stationary scatterers located near the sediment interface. Less commonly, a SAS system may be used to observe scattering features located above the sonar in the water column. The Undersea Remote Sensing (USRS) project, sponsored by the Office of Naval Research, was a collaborative Directed Research Initiative (DRI) focused on studying dynamic estuarine water column features. During the USRS DRI, researchers from multiple institutions gathered to observe tidal features at various estuaries along the coast of the United States using both in situ and remote sensing techniques, including SAS. The first studied estuary was the mouth of the Connecticut River (CTR). Data captured by a SAS system deployed during a tidal event were post-processed to create three-dimensional observations of the structure of the leading edge of the CTR's ebb plume front. From these observations, lobed structures similar in scale to previously reported instabilities are revealed, with the present observations providing additional insight regarding the structure of the bubble distribution behind the front. Velocity estimates of plume features were also determined from SAS data and shown to compare favorably with concurrent marine radar estimates.

Identifying sound-scattering organisms is a perennial challenge in fisheries acoustics. Most practitioners classify backscatter based on direct sampling, frequency-difference thresholds, and expert judgement, then echo-integrate at a single frequency. However, this approach struggles with species mixtures, and discards multi-frequency information when integrating. Inversion methods do not have these limitations, but are not widely used because species identifications are often ambiguous and the algorithms are complicated to implement. We address these shortcomings using a probabilistic, Bayesian inversion method. Like other inversion methods, it handles species mixtures, uses all available frequencies, and extends naturally to broadband signals. Unlike previous approaches, it leverages Bayesian priors to rigorously incorporate information from direct sampling and biological knowledge, constraining the inversion and reducing ambiguity in species identification. Because it is probabilistic, a well-specified model should not produce solutions that are both wrong and confident. The model is based on physical scattering processes, so its output is fully interpretable, unlike some machine learning methods. Finally, the approach can be implemented using existing Bayesian libraries and is easily parallelized for large datasets. We present examples using simulations and field data from the Gulf of Alaska, and discuss possible applications and extensions of the method.

Broadband echosounders measure the scattering response of an organism over a range of frequencies. When compared with acoustic scattering models, this response can provide insight into the type of organism measured. Here, we train the k-Nearest Neighbors algorithm using scattering models and use it to group target spectra (25–40 kHz) measured in the mesopelagic near the New England continental shelf break. Compared to an unsupervised approach, this creates groupings defined by their scattering physics and does not require significant tuning. The model classifies human-annotated target spectra as gas-bearing organisms (at, below, or above resonance) or fluid-like organisms with a weighted F1-score of 0.90. Class-specific F1-scores varied — the F1-score exceeded 0.89 for all gas-bearing organisms, while fluid-like organisms were classified with an F1-score of 0.73. Analysis of classified target spectra provides insight into the size and distribution of organisms in the mesopelagic and allows for the assessment of assumptions used to calculate organism abundance. Organisms with resonance peaks between 25 and 40 kHz account for 43% of detections, but a disproportionately high fraction of volume backscatter. Results suggest gas bearing organisms account for 98.9% of volume backscattering concurrently measured using a 38 kHz shipboard echosounder between 200 and 800 m depth.

Recent studies using acoustic techniques suggest that the biomass of mesopelagic fishes may be an order of magnitude higher than previously estimated from trawls. However, there is uncertainty surrounding these estimates, which are derived from shipboard echosounder measurements using necessary, but poorly constrained, assumptions. Here, an echosounder is used to measure individual target strengths at depth. These measurements are used to infer mesopelagic organism density through echo-counting. Measured target strengths are used to estimate organism density by inverting shipboard echosounder measurements. The two sampling methods agree well, but highlight the importance of accurate target strength measurements.

Recent estimates based on shipboard echosounders suggest that 50% or more of global fish biomass may reside in the mesopelagic zone (depths of ~200–1000 m). Nonetheless, little is known about the acoustic target strengths (TS) of mesopelagic animals because ship-based measurements cannot resolve individual targets. As a result, biomass estimates of mesopelagic organisms are poorly constrained. Using an instrumented tow-body, broadband (18–90 kHz) TS measurements were obtained at depths from 70 to 850 m. A comparison between TS measurements at-depth and values used in a recent global estimate of mesopelagic biomass suggests lower target densities at most depths.

Integrated instrumentation packages are an attractive option for environmental and ecological monitoring at marine energy sites, as they can support a range of sensors in a form factor compact enough for the operational constraints posed by energetic waves and currents. Here we present details of the architecture and performance for one such system — the Adaptable Monitoring Package — which supports active acoustic, passive acoustic, and optical sensing to quantify the physical environment and animal presence at marine energy sites. we describe cabled and autonomous deployments and contrast the relatively limited system capabilities in an autonomous operating mode with more expansive capabilities, including real-time data processing, afforded by shore power or in situ power harvesting from waves. Across these deployments, we describe sensor performance, outcomes for biological target classification algorithms using data from multibeam sonars and optical cameras, and the effectiveness of measures to limit biofouling and corrosion. On the basis of these experiences, we discuss the demonstrated requirements for integrated instrumentation, possible operational concepts for monitoring the environmental and ecological effects of marine energy converters using such systems, and the engineering trade-offs inherent in their development. Overall, we find that integrated instrumentation can provide powerful capabilities for observing rare events, managing the volume of data collected, and mitigating potential bias to marine animal behavior. These capabilities may be as relevant to the broader oceanographic community as they are to the emerging marine energy sector.

Accurate measurements of sea ice thickness are critical to better understand climate change, to provide situational awareness in ice-covered waters, and to reduce risks for communities that rely on sea ice. Nonetheless, remotely measuring the thickness of sea ice is difficult. The only regularly employed technique that accurately measures the full ice thickness involves drilling a hole through the ice. Other presently used methods are either embedded in or through the ice (e.g., ice mass balance buoys) or calculate thickness from indirect measurements (e.g., ice freeboard from altimetry; ice draft using sonars; total snow and ice thickness using electromagnetic techniques). Acoustic techniques, however, may provide an alternative approach to measure the total ice thickness. Here laboratory-grown sea ice thicknesses, estimated by inverting the time delay between echoes from the water–ice and ice–air interfaces, are compared to those measured using ice cores. A time-domain model capturing the dominant scattering mechanisms is developed to explore the viability of broadband acoustic techniques for measuring sea ice thickness, to compare with experimental measurements, and to investigate optimal frequencies for in situ applications. This approach decouples ice thickness estimates from water column properties and does not preclude ice draft measurements using the same data.

Active acoustic sensors are widely used in oceanographic and environmental studies. Although many have nominal operating frequencies above the range of marine mammal hearing, they can produce out-of-band sound that may be audible to marine mammals. Acoustic emissions from four active acoustic transducers were characterized and compared to marine mammal hearing thresholds. All four transducers had nominal operating frequencies above the reported upper limit of marine mammal hearing, but produced measurable sound below 160 kHz. A spatial map of the acoustic emissions of each sonar is used to evaluate potential effects on marine mammal hearing when the transducer is continuously operated from a stationary platform. Based on the cumulative sound exposure level metric, the acoustic emissions from the transducers are unlikely to cause temporary threshold shifts in marine mammals, but could affect animal behavior. The extent of audibility is estimated to be, at most, on the order of 100 m.

Flow-noise resulting from oceanic turbulence and interactions with pressure-sensitive transducers can interfere with ambient noise measurements. This noise source is particularly important in low-frequency measurements (f < 100 Hz) and in highly turbulent environments such as tidal channels. This work presents measurements made in the Chacao Channel, Chile, and in Admiralty Inlet, Puget Sound, WA. In both environments, peak currents exceed 3 m/s and pressure spectral densities attributed to flow-noise are observed at frequencies up to 500 Hz. At 20 Hz, flow-noise exceeds mean slack noise levels by more than 50 dB. Two semi-empirical flow-noise models are developed and applied to predict flow-noise at frequencies from 20 to 500 Hz using measurements of current velocity and turbulence. The first model directly applies mean velocity and turbulence spectra while the second model relies on scaling arguments that relate turbulent dissipation to the mean velocity. Both models, based on prior formulations for infrasonic (f < 20 Hz) flow-noise, agree well with observations in Chacao Channel. In Admiralty Inlet, good agreement is shown only with the model that applies mean velocity and turbulence spectra, as the measured turbulence violates the scaling assumption in the second model.

Tidally driven currents and bed stresses can result in noise generated by moving sediments. At a site in Admiralty Inlet, Puget Sound, Washington State (USA), peak bed stresses exceed 20 Pa. Significant increases in noise levels are attributed to mobilized sediments at frequencies from 4–30 kHz with more modest increases noted from 1–4 kHz. Sediment-generated noise during strong currents masks background noise from other sources, including vessel traffic. Inversions of the acoustic spectra for equivalent grain sizes are consistent with qualitative data of the seabed composition. Bed stress calculations using log layer, Reynolds stress, and inertial dissipation techniques generally agree well and are used to estimate the shear stresses at which noise levels increase for different grain sizes. Regressions of the acoustic intensity versus near-bed hydrodynamic power demonstrate that noise levels are highly predictable above a critical threshold despite the scatter introduced by the localized nature of mobilization events.

One calendar year of Automatic Identification System (AIS) ship-traffic data was paired with hydrophone recordings to assess ambient noise in northern Admiralty Inlet, Puget Sound, WA (USA) and to quantify the contribution of vessel traffic. The study region included inland waters of the Salish Sea within a 20 km radius of the hydrophone deployment site. Spectra and hourly, daily, and monthly ambient noise statistics for unweighted broadband (0.02–30 kHz) and marine mammal, or M-weighted, sound pressure levels showed variability driven largely by vessel traffic. Over the calendar year, 1363 unique AIS transmitting vessels were recorded, with at least one AIS transmitting vessel present in the study area 90% of the time. A vessel noise budget was calculated for all vessels equipped with AIS transponders. Cargo ships were the largest contributor to the vessel noise budget, followed by tugs and passenger vessels. A simple model to predict received levels at the site based on an incoherent summation of noise from different vessels resulted in a cumulative probability density function of broadband sound pressure levels that shows good agreement with 85% of the temporal data.