Passive ocean acoustic tomography in shallow water

Li, Fenghua; Yang, Xishan; Zhang, Yanjun; Luo, Wei; Gan, Weiming

doi:10.1121/1.5099350

Cited by 25 publications

(9 citation statements)

References 30 publications

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“…By Equation (11), the second principle to divide the vertical can be summarized: every layer should be divided to include roughly the same ray length to minimize the inversion errors. At the same time, the third principle can be inferred that inversion error decreases as the layer number increases.…”

Section: Comparison Of S2-s3mentioning

confidence: 99%

“…The CAT system developed by the Hiroshima University Acoustic Tomography Group has been widely used for oceanographic observation since 1995 [6]. Plenty of experiments have been conducted to measure depth-averaged water temperature or map temperature distribution vertically and horizontally with the CAT system [7][8][9][10][11][12][13]. Syamsudin et al obtained a five-layer-averaged water temperature and flow velocity of the vertical profile successfully in the Bali Strait using two acoustic systems.…”

Section: Introductionmentioning

confidence: 99%

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Layer-Averaged Water Temperature Sensing in a Lake by Acoustic Tomography with a Focus on the Inversion Stratification Mechanism

Xue

Xie

et al. 2021

Sensors

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Continuous sensing of water parameters is of great importance to fluid dynamic progress study in oceans, coastal areas and inland waters. The acoustic tomography technique can perform water temperature field measurements horizontally and vertically using sound wave travel information. The layer-averaged water temperature can also be measured with the acoustic tomography method. However, investigations focusing on the stratified mechanism, which consists of stratification form and its influence on inversion error, are seldom performed. In this study, an acoustic tomography experiment was carried out in a reservoir along two vertical slices to observe the layer-averaged water temperature. Specifically, multi-path sound travel information is identified through ray tracing using high-precision topography data obtained via a ship-mounted ADCP during the experiment. Vertical slices between sound stations are divided into different layers to study layer division inversion methods in different preset types. The inversion method is used to calculate the average water temperature and inversion temperature error of every layer. Different layer methods are studied with a comparison of results. The layer division principle studied in this paper can be used for layer-averaged water temperature sensing with multi-path sound transmission information.

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Section: Comparison Of S2-s3mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Layer-Averaged Water Temperature Sensing in a Lake by Acoustic Tomography with a Focus on the Inversion Stratification Mechanism

Xue

Xie

et al. 2021

Sensors

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show abstract

“…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;).…”

Section: Introductionmentioning

confidence: 99%

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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“…Its primary objective was to investigate the interaction mechanism between the acoustic field and the water bodies. It is shown that the mutual correlation function and Green's function of marine environmental noise have the similarity of arrival time structure, based on which some scholars proposed the idea of using marine environmental noise for passive acoustic tomography, and the idea was realised by experimental observation (Gasparini et al, 1997;Fried et al, 2013;Li et al, 2019). The presence of mesoscale processes such as ocean fronts/vortices in the oceans has led to the development of acoustic tomography for horizontally varying environmental (Carrière and Hermand, 2008;Yang et al, 2022);.…”

Section: Introductionmentioning

confidence: 99%

Enhancing ocean environment prediction in Yellow Sea through targeted observation using ocean acoustic tomography

Baolong,

Jingyi,

Wuhong

et al. 2023

Front. Mar. Sci.

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Ocean Acoustic Tomography (OAT) is an efficient and economical marine acoustic observation technique. Targeted observation is an appealing procedure to reduce the uncertainty of ocean environment prediction through additional observation. This study aimed to assess the validity of OAT as an observation method for targeted observation. OAT based on Niche Genetic Algorithm was employed to extract sound speed and temperature profiles from acoustic transmission time, utilizing data from the 2019 Yellow Sea experiment. The inversion results were compared with measurement data, which are found to be accurate and reliable. To further evaluate OAT as targeted observation method, the vertical bias structure of OAT was added on synchronous measurement data in the sensitive area of targeted observation to simulate OAT observation in sensitive area. This simulated data was then incorporated into a 3D-Var assimilation system to improve the short-term prediction of the target region. Comparing the predictions derived with the measurement data at the verification time, it shows that the simulated OAT observation improved the quality of target region prediction, indicating that OAT can be an effective observation method for targeted observation. An Observing System Simulation Experiment was conducted to assess the impact of OAT characteristics on prediction improvement. The results show that both adding observation nodes and extending the observation duration have positive effects, while extending the observation duration performs better.

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Passive ocean acoustic tomography in shallow water

Cited by 25 publications

References 30 publications

Layer-Averaged Water Temperature Sensing in a Lake by Acoustic Tomography with a Focus on the Inversion Stratification Mechanism

Layer-Averaged Water Temperature Sensing in a Lake by Acoustic Tomography with a Focus on the Inversion Stratification Mechanism

Using Ocean Ambient Sound to Measure Local Integrated Deep Ocean Temperature

Enhancing ocean environment prediction in Yellow Sea through targeted observation using ocean acoustic tomography

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