Long-term noise interferometry analysis in the northeast Pacific Ocean

Ragland, John; Abadi, Shima; Sabra, Karim G.

doi:10.1121/10.0009232

Cited by 8 publications

(4 citation statements)

References 32 publications

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“…Spectral content of wind generated noise has previously been studied (McCreery et al, 1993). The cross-correlations of ambient sound for these specific hydrophones have previously been demonstrated to consistently converge to the empirical Green's function between the hydrophones over 6 years of studied ambient sound (Ragland, Abadi, & Sabra, 2022). These passive estimates of the Green's function have multiple acoustic arrivals that correspond to multi-path propagation through the water column.…”

Section: Estimating Empirical Green's Function From Ambient Noisementioning

confidence: 99%

“…It has previously been shown that, due to the small sensor separation relative to the depth of the water column, ray‐based methods provide relevant context to acoustic propagation for this environment (Ragland & Abadi, 2022b; Ragland, Abadi, & Sabra, 2022). The first three acoustic rays are shown in Figure 1b, which are simulated with Bellhop (Porter, 2011) using a sound‐speed profile computed from HYCOM.…”

Section: Estimating Empirical Green's Function From Ambient Noisementioning

confidence: 99%

“…In the ocean, ambient noise interferometry has been experimentally demonstrated to estimate the Green's function for a diverse set of environments and illuminating sound sources (Brooks & Gerstoft, 2009; Brown et al., 2014; Fried et al., 2008; F. Li et al., 2019; Ragland, Abadi, & Sabra, 2022; Roux & Kuperman, 2004; K. Woolfe & Sabra, 2015;). Estimating oceanographic variables with ambient noise interferometry requires the accurate estimation of the Green's function between the sensors and also solving the inverse estimation problem that can estimate environmental parameters from acoustic features.…”

Section: Introductionmentioning

confidence: 99%

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Using Ocean Ambient Sound to Measure Local Integrated Deep Ocean Temperature

Ragland,

Abadi,

Sabra

2024

Geophysical Research Letters

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Measuring the temperature changes of the deep ocean will be critical to understanding how the earth system will respond to climate change. In this work, we present a method for measuring the depth‐averaged, deep ocean temperature at local (∼3 km) spatial scales using passive estimates of acoustic propagation. These passive acoustic estimates of deep ocean temperature can be used with existing and future passive acoustic monitoring infrastructure to provide complimentary observations of the ocean to in situ measurements, and could be particularly useful in areas of poor ocean observation coverage. Using 8 years of ambient sound data, we demonstrate that the passive estimates agree with global ocean models and measurements by ARGO floats. The rms difference between the HYCOM ocean model is shown to be 0.13°C, and the rms difference between ARGO measurements is shown to be 0.086°C.

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Section: Estimating Empirical Green's Function From Ambient Noisementioning

confidence: 99%

Section: Estimating Empirical Green's Function From Ambient Noisementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Using Ocean Ambient Sound to Measure Local Integrated Deep Ocean Temperature

Ragland,

Abadi,

Sabra

2024

Geophysical Research Letters

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“…These false positives were reliable for documenting these underwater sounds and were annotated as "Passing ship" acoustic events. Ships were only annotated in this way if they exhibited the same ship event structure observed in the long-term spectral average display by other studies (Ragland et al, 2022). Mid-frequency active sonar was annotated by selecting contours from the whistle and moan detector.…”

Section: Annotation Of Acoustic Eventsmentioning

confidence: 99%

Acoustic indices respond to specific marine mammal vocalizations and sources of anthropogenic noise

Ferguson¹,

Clayton

Sakai

2023

Front. Mar. Sci.

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Using passive acoustic methods for biodiversity conservation and effective ecosystem monitoring is hindered by laborious, human-mediated processes of accurately identifying biologic and anthropogenic sounds within large datasets. Soundscape ecology provides a potential means of addressing this need through the use of automated acoustic-based biodiversity indices, which show promise in representing biodiversity in terrestrial environments. However, the direct relationship between specific underwater sounds and acoustic index measurements are largely unexplored. Using passive acoustic data collected from three broadband hydrophones within the Ocean Observatories Initiative’s cabled arrays in the Pacific northwest, we identified periods of vocalizing marine mammals and sources of anthropogenic noise. Automated calculations of seven acoustic indices were compared were compared across biologic and anthropogenic sound type and call parameters. Although several index measurements did not vary significantly, the Acoustic Complexity Index (ACI) measurements increased in response to echolocation clicks from sperm whales (Physeter macrocephalus) and burst pulses originating from unidentified delphinid species. Measurements of the Bioacoustic Index (BI) decreased dramatically in responses sperm whale echolocation clicks, a more obvious trend when loud clicks were parsed from moderate and quite clicks. Correlations coefficient and confidence interval values between ACI and BI measurements and call characteristics from sperm whales indicate a moderate to strong relationship, which was not found in correlations with delphnid calls. A generalized linear mixed-effect model indicated multiple species and sound types contribute significantly to the variation of several index measurements. Noise generated by passing ships consistently resulted in decreased values for the Normalized Difference Soundscape Index (NDSI) and Total Entropy (H) as compared to quiet periods and periods with vocalizing marine mammals. These findings provide information on the relationship between several acoustic indices and specific underwater sounds produced by marine mammals and anthropogenic sources. This ground-truthing endeavor expands the understanding of acoustic indices and their potential use as a tool for conservation and ecosystem health management purposes.

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Mesh generation for underwater acoustic modeling with KRAKEN

Monteiro

Oliveira

2023

Advances in Engineering Software

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Long-term noise interferometry analysis in the northeast Pacific Ocean

Cited by 8 publications

References 32 publications

Using Ocean Ambient Sound to Measure Local Integrated Deep Ocean Temperature

Using Ocean Ambient Sound to Measure Local Integrated Deep Ocean Temperature

Acoustic indices respond to specific marine mammal vocalizations and sources of anthropogenic noise

Mesh generation for underwater acoustic modeling with KRAKEN

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