Ocean Observatories Initiative Research Articles

This study characterizes the statistical dependence of low-frequency ambient sound on wind speed using 8 years of Ocean Observatories Initiative hydrophone data. Data from two bottom-mounted hydrophones, sampled at 200 Hz, are compared to a National Oceanic and Atmospheric Administration surface winds model. One hydrophone is on the continental slope and one is in open ocean. Wind dependence on ambient sound levels is reported for both locations across all studied frequencies (0.1-90 Hz). A piecewise, log-linear model is fit to ambient sound and wind speed, and different regions of wind dependence are discussed. Directional surface wave spectra from a nearby buoy are compared with acoustic measurements below 1.2 Hz. Time-frequency characteristics in acoustic data are largely explained by local surface spectra.

The Kauai Beacon (KB), which began regular transmissions in March 2023, presents an opportunity to leverage existing hydrophones for ocean basin acoustic observations. This study examines KB receptions at the Ocean Observatories Initiative (OOI) hydrophones. Positive receptions are reported at eight of the 11 hydrophone locations. Observed arrivals are compared to simulated acoustic propagation. Analysis reveals that four OOI hydrophone locations demonstrate consistent arrivals suitable for tracking acoustic travel-time fluctuations, making them promising candidates for traditional ocean acoustic tomography applications. Analysis of the complex envelope statistics shows that acoustic simulation with internal waves effectively reproduces the observed arrivals at most locations. A notable exception is the Oregon Offshore hydrophone, bottom-mounted on the continental slope, where measured receptions lack the anticipated increase in acoustic energy associated with lowest mode order arrivals. This suggests enhanced mode coupling beyond standard Garrett-Munk energy internal wave energy predictions. This work demonstrates the potential for utilizing existing passive acoustic monitoring infrastructure for ocean basin observations and provides insights into single-hydrophone, long-range acoustic propagation that can inform future developments in acoustically observing ocean basins.

Gridded, high-resolution ocean observatories initiative profiler data from the Washington continental slope, 2014-2025.

Ocean-bottom distributed acoustic sensing (DAS) can measure strain induced by seismo-acoustic waves. Among them, T waves travel in the water column at the speed of sound and are expected to propagate as modes. DAS dense time and space sampling gives access to dispersion curves in the frequency-wavenumber domain. In DAS data acquired by the Ocean Observatory Initiative on Oregon shore, Scholte waves dominate the 0.1-1.5 Hz frequency band. We identify a cable section where Scholte-wave energy forms marked power-law shape regions in the frequency-wavenumber domain. We use these dispersion curves for deterministic inversion of a power-law shear-speed profile and of a constant seabed density based on an analytic model. We focus on T waves from a regional earthquake in the 2-30 Hz frequency band. Far offshore, the dispersion curves of four T-wave modes are visible, but only one mode is visible where seabed inversion is possible. This T-wave mode is used for compressional-wave speed inversion based on analytical modes in a fluid-fluid-solid waveguide and using seabed density from Scholte-wave inversion. We discuss the differences between theoretical modes in a fluid-fluid-solid waveguide and in a fluid-solid-solid waveguide with a sediment shear-speed lower than the ocean sound speed.

Detecting and locating marine mammals is essential for understanding their behavior and supporting conservation efforts. Acoustic methods complement visual surveys and tagging, which are often limited in spatial and temporal coverage. Fin whales are particularly suited for acoustic monitoring due to their stereotypical 20 Hz vocalizations. Distributed Acoustic Sensing (DAS) offers a promising addition to hydrophone data, using fiber-optic cables as sensors for continuous, high-resolution monitoring over distances up to about 100 km. In November 2021, a DAS dataset was collected using the Ocean Observatories Initiative Regional Cabled Array, capturing valuable data on fin whale vocalizations. This dataset includes measurements from two cables with 2 m channel spacing, spanning 65-95 km. This study evaluates various approaches-including signal-to-noise ratio estimation, matched filtering, Gabor filtering, and noise envelope subtraction-for enhancing and denoising fin whale calls in DAS data. A method that combines matched filtering and envelope subtraction is most effective at detecting even low SNR fin whale calls and obtaining arrival times. Overall, this study highlights the potential of DAS array processing to significantly improve signal-to-noise ratios and enhance detection capabilities for monitoring fin whales.

The Kauai Beacon is an ocean acoustic tomography source off the coast of Kauai that began regularly transmitting in March 2023. In this presentation, positive acoustic receptions of the Kauai Beacon are measured by the Ocean Observatories Initiative (OOI) hydrophones and compared to acoustic arrivals simulated with the parabolic equation method for the first 20 months of regular transmissions. Positive receptions of the Kauai Beacon are reported for eight of the eleven OOI hydrophones. The structure of the observed acoustic arrivals over the first 20 months is compared to simulated acoustic arrivals, and the arrival envelope statistics are compared to simulation. The Kauai Beacon stands to serve as a source of opportunity for any passive-acoustic monitoring infrastructure within its acoustic paths to measure ocean basin acoustic propagation and infer oceanographic variables such as water temperature. This presentation provides the necessary context to develop future methods to acoustically infer ocean temperature with single hydrophone receptions of the Kauai Beacon. [Work supported by ONR.]

Marine seismic reflection surveys provide an abundance of acoustic data over survey regions and surrounding areas. The data from these surveys, in addition to passive observations made possible with networks like the Ocean Observatories Initiative (OOI), provide a wealth of acoustic propagation data in a variety of environments. Furthermore, the repeatability of airgun array shots yields a minimally variable source from which to extract more precise trends. In this work, we consider data from two seismic surveys, MGL1905 and MGL2104, during which a 6600 in3 airgun array is fired every 37.5 m along multiple survey lines extending 10s to 100s of kilometers. The data collected on the OOI hydrophones is analyzed to quantify long-term trends in the ambient soundscape. Additionally, characteristics and artifacts in the data are examined for possible usefulness in extracting details about the propagating environment. [Work supported by ONR.]

Extensive monitoring of acoustical activities is important for many fields, including biology, security, and ocean and Earth science. Distributed acoustic sensing (DAS) is an evolving technique for continuous, wide-coverage measurements of mechanical vibrations across oceans. DAS illuminates a fiber-optic cable with laser pulses and measures the backscattered wave due to small random variations in the refractive index of the material. Specifically, DAS uses coherent optical interferometry to measure the phase difference of the backscattered wave from adjacent locations along the fiber. External stimuli, such as mechanical strain due to acoustic wavefields impinging on the fiber-optic cable, modulate the backscattered wave. Hence, the differential phase measurements of the optical backscatter are proportional to the underlying physical quantities of the surrounding wavefield. Continuous measurement of the backscattered electromagnetic signal provides a distributed sensing modality for the external acoustic wavefield that extends spatially along the fiber. We provide a comprehensive overview of DAS technology and detail the underlying physics, from electromagnetic to mechanical and eventually acoustic quantities. We explain the effect of DAS acquisition parameters in signal processing and show the potential of DAS for sound source detection on data collected from the Ocean Observatories Initiative, DOI: https://doi.org/10.58046/5J60-FJ89.

In the frequency band between 1 and 10 Hz, ambient sound in the ocean has a global pattern in the power spectral density that is driven by local surface gravity waves and is highly correlated to wind speeds. At low frequencies above 10 Hz, other source mechanisms dominate ambient sound. In thispresentation, surface buoy measurements, model estimates, and satellite-based observations of wind speed are compared to spectral levels measured by the five low-frequency hydrophones that are part of the Ocean Observatories Initiative Cabled Array. Features of the spectrogram are categorized and associated with wind observations. The ambient sound spectral levels are linearly separable by wind speed at frequencies below 5 Hz. Lastly, a general frequency-temporal structure of spectral levels due to wind events is presented and discussed. [Work supported by ONR.]

Understanding the behavior and distribution of marine mammals such as fin whales is essential for conservation efforts and population recovery assessments. Distributed acoustic sensing (DAS) offers an innovative and scalable solution by transforming submarine fiber optic cables into dense arrays of acoustic sensors. Over 4 days in November 2021, a public DAS dataset was collected using the Ocean Observatories Initiative Regional Cabled Array off the coast of Oregon, recording tens of thousands of fin whale calls during their breeding season. Previous work demonstrated the feasibility of automated detection using matched filtering, Gabor filtering, and signal-to-noise ratio estimation. Building on these methods, this study aims to obtain a full set of localizations for the experiment. To achieve this, detected calls are automatically associated across DAS channels through a coarse grid search, followed by a least-squares time difference of arrival (TDOA) method to estimate call positions. These techniques are tested on representative subsets of the dataset, providing a foundation for long-term studies on fin whales using DAS. The resulting catalog of localizations and tracks can address questions such as fin whale distribution across the shelf and upper continental slope, net movement direction, and spatial organization of calling individuals. [Work supported by ONR.]

Distributed Acoustic Sensing (DAS) technology enables continuous monitoring of acoustic vibrations along fiber-optic cables, providing high-resolution spatial and temporal data for marine acoustic applications. This study investigates DAS’s capability for analyzing underwater radiated noise from ships, leveraging 4 days of DAS data collected in November 2021 using two cables from the Ocean Observatories Initiative Regional Cabled Array, extending offshore central Oregon. Data were collected using OptaSense and Silixa interrogators with gauge lengths of either 30 or 50 m and sampling rates ranging from 200 to 1000 Hz. Ship signals were identified in DAS data using Automatic Identification System (AIS) information and analyzed across different fibers and interrogators to assess system performance. Our results demonstrate that large ships are clearly visible in the DAS data within the 10–90 Hz frequency band at ranges exceeding 10 km. Low-frequency filtering extends the detection range, enhancing the ability to monitor ship signals. DAS-derived ship signals are compared with hydrophone data and a propagation model to assess the DAS system's detection capabilities. This study highlights the potential of DAS technology for maritime acoustic monitoring and its complementary role to traditional hydrophone systems in capturing underwater radiated noise by ships.

Abstract Distributed acoustic sensing (DAS) on submarine fiber-optic cables is providing new observational insights into solid Earth processes and ocean dynamics. However, the availability of offshore dark fibers for long-term deployment remains limited. Simultaneous telecommunication and DAS operating at different wavelengths in the same fiber, termed optical multiplexing, offers one solution. In May 2024, we collected a four-day DAS dataset utilizing an L-band DAS interrogator and multiplexing on the submarine cables of the Ocean Observatory Initiative’s Regional Cabled Array offshore central Oregon. Our findings show that multiplexed DAS has no impact on communications and is unaffected by network traffic. Moreover, the quality of DAS data collected via multiplexing matches that of data obtained from dark fiber. With a machine-learning event detection workflow, we detect 31 T waves and the S wave of one regional earthquake, demonstrating the feasibility of continuous earthquake monitoring using the multiplexed offshore DAS. We also examine ocean waves and ocean-generated seismic noise. We note high-frequency seismic noise modulated by low-frequency ocean swell and hypothesize about its origins. The complete dataset is freely available.

The Ocean Observatories Initiative (OOI) provides continuous monitoring of acoustic fields at various locations in the northeast Pacific Ocean, among other types of data. The effects of marine seismic reflection surveys on the ambient soundscape in the vicinity of these hydrophones can be quantified by looking at OOI hydrophone data in conjunction with cruise documentation. Two seismic reflection surveys, MGL1905 and MGL2104, and measurements on three hydrophones at varying depths with 64 kHz sampling rates are considered. The seismic air guns are exhibited to raise the mean ambient sound by up to 30 dB over several one-third octave bands, where the impact varies significantly as a function of range, depth, and other factors. Effects can be observed hundreds of kilometers from the air gun arrays, and shots may be frequent enough that the ambient sound does not return to its pre-cruise background levels between shots. Although range is strongly correlated with these effects, metrics, such as sound exposure level or sound pressure level, can easily vary by 10 dB or more at the same range.

Anthropogenic noise in the ocean is one of the many stressors affecting marine biodiversity. Knowing animals and ships locations is key to conservation efforts. Geophony is also of research interest, as T-phases analysis can help to characterize ocean seismicity and measure ocean temperature. However, offshore passive acoustic monitoring remains challenging and expensive, necessitating continuous advancements in technology. Distributed Acoustic Sensing (DAS) is one possible complement that leverages existing infrastructure to provide continuous acoustic data from the seafloor in near-real-time, at an onshore facility. DAS uses fiber-optic cables as sensors, offering capabilities comparable to an array of thousands of directional hydrophones, whose sampling frequencies depend on the longest probing distance. Various datasets are presented here, including those from the fiber connection between Seattle and Bothell, the Ocean Observatories Initiative’s Regional Cable Array off the coast of Oregon, and the MARS cable in Monterey Bay. In this virtual lab tour, we provide an insight into the workflow, from data collection to processing and data analysis. The results of this research at the University of Washington have led to new observational efforts on land, ice, and underwater, spanning fields as diverse as oceanography, seismology, engineering, and marine ecology. [Work partially supported by ONR]

Distributed Acoustic Sensing (DAS) technology enables continuous monitoring of acoustic vibrations along fiber optic cables, providing high-resolution spatial and temporal data. This study explores the application of DAS technology for analyzing underwater radiated noise from ships. In November 2021, four days of DAS data were collected using two cables from the Ocean Observatories Initiative Regional Cabled Array, extending offshore central Oregon. Numerous ship passages occurred over these cables, with information available through the Automatic Identification System (AIS). DAS data were collected using two different interrogators on two fibers in each cable, providing an opportunity to investigate the differences in ship noise detected on different fibers within the same cable and across different DAS systems with varying configurations. Preliminary analysis of two large ships shows that their noise is clearly detected in the DAS measurements. By combining these measurements with AIS data, we can accurately locate the receiving channels on the cable. This talk will expand on these observations to perform a comparative analysis of the measurements across different fibers and interrogators. These findings demonstrate the capability of DAS technology in maritime acoustic monitoring and its potential to enhance our understanding of underwater noise pollution.

Abstract Axial Seamount, an extensively instrumented submarine volcano, lies at the intersection of the Cobb–Eickelberg hot spot and the Juan de Fuca ridge. Since late 2014, the Ocean Observatories Initiative (OOI) has operated a seven-station cabled ocean bottom seismometer (OBS) array that captured Axial’s last eruption in April 2015. This network streams data in real-time, facilitating seismic monitoring and analysis for volcanic unrest detection and eruption forecasting. In this study, we introduce a machine learning (ML)-based real-time seismic monitoring framework for Axial Seamount. Combining both supervised and unsupervised ML and double-difference techniques, we constructed a comprehensive, high-resolution earthquake catalog while effectively discriminating between various seismic and acoustic events. These events include earthquakes generated by different physical processes, acoustic signals of lava–water interaction, and oceanic sources such as whale calls. We first built a labeled ML-based earthquake catalog that extends from November 2014 to the end of 2021 and then implemented real-time monitoring and seismic analysis starting in 2022. With the rapid determination of high-resolution earthquake locations and the capability to track potential precursory signals and coeruption indicators of magma outflow, this system may improve eruption forecasting by providing short-term constraints on Axial’s next eruption. Furthermore, our work demonstrates an effective application that integrates unsupervised learning for signal discrimination in real-time operation, which could be adapted to other regions for volcanic unrest detection and enhanced eruption forecasting.

Abstract The subpolar North Atlantic plays an outsized role in the atmosphere‐to‐ocean carbon sink. The central Irminger Sea is home to well‐documented deep winter convection and high phytoplankton production, which drive strong seasonal and interannual variability in regional carbon cycling. We use observational data from moored carbonate chemistry system sensors and annual turn‐around cruise samples at the Ocean Observatories Initiative's Irminger Sea Array to construct a near‐continuous time series of mixed layer total dissolved inorganic carbon (DIC), pCO2, and total alkalinity from summer 2015 to summer 2022. We use these carbonate chemistry system time series to deconvolve the physical and biological drivers of surface ocean carbon cycling in this region on seasonal, annual, and interannual time scales. We find high annual net community production within the seasonally varying mixed layer, averaging 9.8 ± 1.6 mol m−2 yr−1 with high interannual variability (range of 6.0–13.9 mol m−2 yr−1). The highest daily net community production rates occur during the late winter and early spring, prior to the observed high chlorophyll concentrations associated with the spring phytoplankton bloom. As a result, the winter and early spring play a much larger role in biological carbon export from the mixed layer than traditionally thought.

The field of oceanography is transitioning from data-poor to data-rich, thanks in part to increased deployment of in-situ platforms and sensors, such as those that instrument the US-funded Ocean Observatories Initiative (OOI). However, generating science-ready data products from these sensors, particularly those making biogeochemical measurements, often requires extensive end-user calibration and validation procedures, which can present a significant barrier. Openly available community-developed and -vetted Best Practices contribute to overcoming such barriers, but collaboratively developing user-friendly Best Practices can be challenging. Here we describe the process undertaken by the NSF-funded OOI Biogeochemical Sensor Data Working Group to develop Best Practices for creating science-ready biogeochemical data products from OOI data, culminating in the publication of the GOOS-endorsed OOI Biogeochemical Sensor Data Best Practices and User Guide. For Best Practices related to ocean observatories, engaging observatory staff is crucial, but having a “user-defined” process ensures the final product addresses user needs. Our process prioritized bringing together a diverse team and creating an inclusive environment where all participants could effectively contribute. Incorporating the perspectives of a wide range of experts and prospective end users through an iterative review process that included “Beta Testers’’ enabled us to produce a final product that combines technical information with a user-friendly structure that illustrates data analysis pipelines via flowcharts and worked examples accompanied by pseudo-code. Our process and its impact on improving the accessibility and utility of the end product provides a roadmap for other groups undertaking similar community-driven activities to develop and disseminate new Ocean Best Practices.

Ocean Observatories Initiative Facility Board Administrative Support Office (NSF)

Marine seismic reflection surveys provide a dense and abundant dataset covering a large region of geological interest in the ocean. These data provide an opportunity for acoustic analysis with varying environmental characteristics, both in the water column and the seabed. In a typical survey, an airgun array is fired tens to hundreds of thousands of times, and hundreds of receiver channels record the acoustic signal reflected from the seabed after each shot. Additionally, the high amplitude signal broadcast from airgun arrays used in these surveys may be measured passively by hydrophones located close to the survey. In this work, we consider the data measured by Ocean Observatories Initiative (OOI) hydrophones adjacent to two seismic surveys, MGL1905, and MGL2104. In each case, a 6600 in3 airgun array is fired ∼every 37.5 m along multiple survey lines extending 10s to 100s of kilometers. Each survey generates multiple terabytes of acoustic data, and many of the shots are also captured by OOI hydrophones. This work aims to combine these two datasets to evaluate the acoustic behavior of airgun shots over a variety of conditions and examine the relationship between various environmental factors and acoustic propagation behavior. [Work supported by ONR.]