Journal articles: 'Underwater sea ambient noise'

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Halliday, William D., Matthew K. Pine, and Stephen J. Insley. "Underwater noise and Arctic marine mammals: review and policy recommendations." Environmental Reviews 28, no. 4 (December 2020): 438–48. http://dx.doi.org/10.1139/er-2019-0033.

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Underwater noise is an important issue globally. Underwater noise can cause auditory masking, behavioural disturbance, hearing damage, and even death for marine animals. While underwater noise levels have been increasing in nonpolar regions, noise levels are thought to be much lower in the Arctic where the presence of sea ice limits anthropogenic activities. However, climate change is causing sea ice to decrease, which is allowing for increased access for noisy anthropogenic activities. Underwater noise may have more severe impacts in the Arctic compared with nonpolar regions due to a combination of lower ambient sound levels and increased sensitivity of Arctic marine animals to underwater noise. Here, we review ambient sound levels in the Arctic, as well as the reactions of Arctic and sub-Arctic marine mammals to underwater noise. We then relate what is known about underwater noise in the Arctic to policies and management solutions for underwater noise and discuss whether Arctic-specific policies are necessary.

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Bagočius, Donatas, and Aleksas Narščius. "Underwater Noise Modeling in Lithuanian Area of the Baltic Sea." Mokslas - Lietuvos ateitis 9, no. 4 (September 11, 2017): 393–99. http://dx.doi.org/10.3846/mla.2017.1063.

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Along with rising awareness of public and scientific societies about environmental and ecological impacts of underwater noise, the need for underwater noise modelling in the shallow Lithuanian area of Baltic Sea emerged. Marine Strategy Framework Directive issues regarding underwater noise indicators refers to possibility of evaluation of Good Environmental State using underwater noise measurements as well as possibility to model underwater noise. Main anthropogenic underwater noise contributor in the Seas is the shipping lanes as known due to date, with no exclusion of Lithuanian Baltic Sea area. In this manuscript, it is presented the methods of development of simplistic underwater ambient noise model purposed for computation of underwater soundscape in shallow area of the Lithuanian Baltic Sea.

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Veeraiyan, Vijayabaskar, Rajendran Velayutham, and Mathews M. Philip. "Frequency Domain Based Approach for Denoising of Underwater Acoustic Signal Using EMD." Journal of Intelligent Systems 22, no. 1 (March 1, 2013): 67–80. http://dx.doi.org/10.1515/jisys-2012-0021.

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Abstract.Underwater communication is usually affected by ambient noise, which may be generated by different sources, such as the wind origin sea-surface sources, ships and under water life. The properties of background noise, which are non-stationary in nature, depend on location, sea depth, wind speed and sound propagation conditions in the area. Overall performance of underwater acoustic instruments can be improved by denoising the underwater signals. This paper proposes a novel denoising method using empirical mode decomposition (EMD) technique. Frequency domain based thresholding has been used to denoise the signal, which involves three steps: (i) EMD is applied to the noisy signal to decompose the signal into intrinsic mode functions (IMFs). (ii) Thresholding is applied to each IMF in the frequency domain to remove the noise. (iii) Thresholded IMFs are added to obtain the denoised signal. Real-time experiments were performed to validate the proposed technique on the basis of the records of the ambient noise data recorded at sea for various wind speed. It was observed that the experimental results are in good agreement with the proposed algorithm under different wind-noise levels.

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MURUGAN, S. SAKTHIVEL, and V. NATARAJAN. "IMPLEMENTATION OF THRESHOLD DETECTION TECHNIQUE FOR EXTRACTION OF COMPOSITE SIGNALS AGAINST AMBIENT NOISES IN UNDERWATER COMMUNICATION USING EMPIRICAL MODE DECOMPOSITION." Fluctuation and Noise Letters 11, no. 04 (December 2012): 1250031. http://dx.doi.org/10.1142/s0219477512500319.

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Acoustic signals transmitted in underwater for distance communication are affected by numerous factors, random events, and corrupted with ambient noise, making them nonlinear and nonstationary in nature. Ambient noises are the background acoustic noises in the sea due to natural and manmade sources like wind, rain, seismic, marine species, harbor activities, motor on the boat, ship traffic, etc. In recent years, the application of Empirical Mode Decomposition (EMD) technique to analyze nonlinear and nonstationary signals has gained importance. In this paper an EMD system is proposed with an algorithm by implementing FFT to identify and extract all the acoustic stationary signals available in the underwater channel that are corrupted due to various ambient noises over a range of 100 Hz to 10 kHz in shallow water region. Further a new threshold detection technique is also incorporated in the algorithm for detection and extraction of composite signals that are not extracted properly. The threshold is calculated using the mean and variance of the noisy signal generated by various ambient noises in the ocean. The algorithm is also validated by transmitting three reference acoustic signals. The proposed EMD approach with threshold detector algorithm identifies and extracts all the signals transmitted along with other stationary signals available in the ocean against various ambient noises.

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Sun, Qindong, and Hongkun Zhou. "An Acoustic Sea Glider for Deep-Sea Noise Profiling Using an Acoustic Vector Sensor." Polish Maritime Research 29, no. 1 (March 1, 2022): 57–62. http://dx.doi.org/10.2478/pomr-2022-0006.

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Abstract An acoustic sea glider has been developed for ambient sea noise measurement and target detection through the deployment of an acoustic vector sensor (AVS). The glider was designed with three cabins connected in sequence and it can dive to depths exceeding 1200m. The AVS fixed on the glider measure acoustic pressure and particle velocities related to undersea noise, and the inner attitude sensors can effectively eliminate the estimation deviation of the direction of arrival. The inherent self-noises of the acoustic sea glider and AVS are presented respectively in respect to the Knudsen spectra of sea noise. Sea trial results indicate that the AVS could work well for undersea noise measurement when the glider is smooth sliding, and the target azimuth estimated by AVS after correction is remarkably consistent with the values measured by the GPS, and direction-finding errors are less than 10 degrees. The research in this paper shows that the acoustic sea glider is able to undertake tasks such as a wide range of underwater acoustic measurement and detection.

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Roth, Ethan H., John A. Hildebrand, Sean M. Wiggins, and Donald Ross. "Underwater ambient noise on the Chukchi Sea continental slope from 2006–2009." Journal of the Acoustical Society of America 131, no. 1 (January 2012): 104–10. http://dx.doi.org/10.1121/1.3664096.

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Kwon, Hyuckjong, Junghun Kim, Jee Woong Choi, Donhyug Kang, Sungho Cho, Seom-Kyu Jung, and Kyeongju Park. "Spatial Coherence Analysis of Underwater Ambient Noise Measured at the Yellow Sea." Journal of the Acoustical Society of Korea 34, no. 6 (November 30, 2015): 432–43. http://dx.doi.org/10.7776/ask.2015.34.6.432.

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Yang, Qiulong, Kunde Yang, and Shunli Duan. "A Method for Noise Source Levels Inversion with Underwater Ambient Noise Generated by Typhoon in Deep Ocean." Journal of Theoretical and Computational Acoustics 26, no. 02 (June 2018): 1850007. http://dx.doi.org/10.1142/s259172851850007x.

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Sea-surface wind agitation can be considered the dominant noise sources whose intensity relies on local wind speed during typhoon period. Noise source levels in previous researches may be unappreciated for all oceanic regions and should be corrected for modeling typhoon-generated ambient noise fields in deep ocean. This work describes the inversion of wind-driven noise source level based on a noise field model and experimental measurements, and the verification of the inverted noise source levels with experimental results during typhoon period. A method based on ray approach is presented for modeling underwater ambient noise fields generated by typhoons in deep ocean. Besides, acoustic field reciprocity is utilized to decrease the calculation amount in modeling ambient noise field. What is more, the depth dependence and the vertical directionality of noise field based on the modeling method and the Holland typhoon model are evaluated and analyzed in deep ocean. Furthermore, typhoons named “Soulik” in 2013 and “Nida” in 2016 passed by the receivers deployed in the western Pacific (WP) and the South China Sea (SCS). Variations in sound speed profile, bathymetry, and the related oceanic meteorological parameters are analyzed and taken into consideration for modeling noise field. Boundary constraint simulated annealing (SA) method is utilized to invert the three parameters of noise source levels and to minimize the objective function value. The prediction results with the inverted noise source levels exhibit good agreement with the measured experiment data and are compared with predicted results with other noise sources levels derived in previous researches.

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Fung, Kathryn, and Julien Bonnel. "Statistical and spatial characteristics of ocean ambient noise up to 1900 Hz on the Chukchi Shelf in the Arctic affected by climate change." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A72. http://dx.doi.org/10.1121/10.0015583.

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This paper analyzes a year of underwater ambient noise data recorded in the Arctic on the Chukchi Shelf as part of the 2016–2017 Canada Basin Acoustic Propagation Experiment (CANAPE). A broadband (50–1900 Hz) statistical study is performed to analyze noise variability and its relationship to environmental drivers, notably the local presence of ice and the presence/absence of the Beaufort duct in the experimental area. Both environmental factors are found to significantly affect the noise levels. Local ice coverage tends to decrease ambient noise at all frequencies, while the presence of the Beaufort duct tends to increase ambient noise for frequencies below 1 kHz. The lowest ambient noise levels are, thus, found when the sea is ice covered, but the duct is absent. Furthermore, the study explores the link between noise level and distant ice drift magnitude. The ambient noise levels are shown to be highly correlated with distant (up to 1400 km) ice drift for frequencies between 300 and 1500 Hz. [Work supported by the Office of Naval Research.]

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Nystuen, Jeffrey A., Marios N. Anagnostou, Emmanouil N. Anagnostou, and Anastasios Papadopoulos. "Monitoring Greek Seas Using Passive Underwater Acoustics." Journal of Atmospheric and Oceanic Technology 32, no. 2 (February 2015): 334–49. http://dx.doi.org/10.1175/jtech-d-13-00264.1.

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AbstractThe Hellenic Center for Marine Research POSEIDON ocean monitoring and forecasting system has included passive underwater acoustic measurements as part of its real-time operations. Specifically, low-duty-cycle long-term passive acoustic listeners (PALs) are deployed on two operational buoys, one off Pylos in the Ionian Sea and the second off Athos in the northern Aegean Sea. The first step toward the quantitative use of passive ambient sound is the classification of the geophysical sources—for example, wind speed and rain rate—from the noise of shipping, from other anthropogenic activities, and from the natural sounds of marine animals. After classification, quantitative measurements of wind speed and precipitation are applied to the ambient sound data. Comparisons of acoustic quantitative measurements of wind speed with in situ buoy anemometer measurements were shown to be within 0.5 m s−1. The rainfall detection and quantification was also confirmed with collocated measurements of precipitation from a nearby coastal rain gauge and operational weather radar rainfall observations. The complicated condition of high sea states, including the influence of ambient bubble clouds, rain, and sea spray under high winds, was sorted acoustically, and shows promise for identifying and quantifying such conditions from underwater sound measurements. Long-term data were used in this study to derive sound budgets showing the percent occurrence of dominant sound sources (ships, marine mammals, wind, and rain), their relative intensity as a function of frequency, and statistical summaries of the retrieved rainfall amounts and wind speeds at the two buoy locations in the Aegean and Ionian Seas.

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Jiang, Cheng, JianLong Li, and Wen Xu. "The Use of Underwater Gliders as Acoustic Sensing Platforms." Applied Sciences 9, no. 22 (November 12, 2019): 4839. http://dx.doi.org/10.3390/app9224839.

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Underwater gliders travel through the ocean by buoyancy control, which makes their motion silent and involves low energy consumption. Due to those advantages, numerous studies on underwater acoustics have been carried out using gliders and different acoustic payloads have been developed. This paper aims to illustrate the use of gliders in underwater acoustic observation and target detection through experimental data from two sea trials. Firstly, the self-noise of the glider is analyzed to illustrate its feasibility as an underwater acoustic sensing platform. Then, the ambient noises collected by the glider from different depths are presented. By estimating the transmission loss, the signal receiving ability of the glider is assessed, and a simulation of target detection probability is performed to show the advantages of the glider over other underwater vehicles. Moreover, an adaptive line enhancement is presented to further reduce the influence of self-noise. Meanwhile, two hydrophones are mounted at both ends of the glider to form a simple array with a large aperture and low energy consumption. Thus, the target azimuth estimation is verified using broadband signals, and a simple scheme to distinguish the true angle from the port‒starboard ambiguity is presented. The results indicate that the glider does have advantages in long-term and large-scale underwater passive sensing.

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Li, Jiemeihui, Yang Shi, Yixin Yang, and Xiaodong Huang. "Noise of Internal Solitary Waves Measured by Mooring-Mounted Hydrophone Array in the South China Sea." Journal of Marine Science and Engineering 10, no. 2 (February 8, 2022): 222. http://dx.doi.org/10.3390/jmse10020222.

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Internal solitary waves in the South China Sea have attracted attention because of their large amplitude and high rate of occurrence. Internal solitary waves have a substantial influence on underwater sound propagation and ambient noise. However, there have seldom been reports on the noise they cause. In this paper, we conducted an internal solitary waves cooperative observation experiment in the South China Sea in 2016. We analyzed the temperature, flow velocity and noise changes induced by internal solitary waves. The power spectra of noise generated by internal solitary waves at frequencies below 100 Hz was almost 20 dB higher than ambient noise. The observed low-frequency noise had uniform harmonics. Combined with the changes of flow velocity, we interpreted the low frequency noise as flow noise induced by vortex-induced vibration of internal solitary waves flowing past the cable mooring system. The noise spectra were related to the position of the cable where the hydrophone was mounted. The closer they were to the middle of the cable, the greater the vibration amplitude, and the stronger the noise. This study provided a passive acoustic monitoring and warning method for high marine currents.

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Yang, L., X. Xu, and P. Berggren. "Spotted seal Phoca largha underwater vocalisations in relation to ambient noise." Marine Ecology Progress Series 683 (February 3, 2022): 209–20. http://dx.doi.org/10.3354/meps13951.

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Animals use different strategies to adjust their vocalisations to compensate for ambient noise interference. This is true for some marine mammals, especially cetaceans, but relatively little is known about this for pinnipeds. We recorded 4 major call types (drum, growl, knock, and sweep) of spotted seals Phoca largha in Liaodong Bay, China, to investigate if seals adjusted their vocalisation parameters in relation to broadband (50-4000 Hz) ambient noise recorded immediately preceding each seal vocalisation. Regression analyses showed that the received level of growls, in both broadband and 1/3-octave bands, centred at 200 and 400 Hz, significantly increased with increasing ambient noise levels. These relationships were not observed in the other 3 call types. Further, regardless of call type, the duration, centroid frequency, and root mean squared bandwidth parameters showed no statistical relationship with noise levels. The noise measured in this study had relatively low broadband levels of 116-132 dB re 1 µPa, and no masking was predicted for any of the 4 call types at 200 and 400 Hz when applying a standard critical ratio approach. It is therefore possible that the ambient noise levels in the study area were not sufficiently loud to induce vocal compensation to avoid masking, but loud enough for the seals to adjust their growl vocalisations. To our knowledge, this study is the first to investigate potential vocal adjustment of spotted seals in relation to ambient noise and is important in light of increasing anthropogenic noise in the marine environment.

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PENG, XUE-LIN, and HONG HAO. "A NUMERICAL STUDY OF DAMAGE DETECTION OF UNDERWATER PIPELINE USING VIBRATION-BASED METHOD." International Journal of Structural Stability and Dynamics 12, no. 03 (May 2012): 1250021. http://dx.doi.org/10.1142/s0219455412500216.

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This paper presents a numerical investigation of the feasibility of condition monitoring of untrenched pipelines at seabed through ambient vibration measurements. A finite element (FE) model is developed to calculate the dynamic responses of pipelines to ambient wave forces. The model takes into consideration the interaction between the ocean waves, submarine pipeline, and seabed. The fluid around the pipeline is simulated using the acoustic fluid elements, while soil is simulated by springs and dashpots. The ambient hydrodynamic force in the marine environment is simulated based on the Joint North Sea Wave Observation Project (JONSWAP) spectrum. The transfer function from the wave surface elevation to the wave force is used to get the wave force spectrum. The dynamic responses of the pipe structure with different assumed damage conditions to the ambient wave forces are calculated. The calculated dynamic responses are assumed as measured ambient vibration data in condition monitoring to extract the pipeline vibration properties, which in turn are used in the FE model updating calculation to identify the pipeline conditions. Different noise levels are introduced into the calculated dynamic responses to simulate uncertainties that may arise from measurement and ambient hydrodynamic environment. The effect of noise levels on the extraction of pipeline vibration properties, and on the identification of the pipeline conditions is investigated.

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Cauchy, Pierre, Karen J. Heywood, Nathan D. Merchant, Bastien Y. Queste, and Pierre Testor. "Wind Speed Measured from Underwater Gliders Using Passive Acoustics." Journal of Atmospheric and Oceanic Technology 35, no. 12 (December 2018): 2305–21. http://dx.doi.org/10.1175/jtech-d-17-0209.1.

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AbstractWind speed measurements are needed to understand ocean–atmosphere coupling processes and their effects on climate. Satellite observations provide sufficient spatial and temporal coverage but are lacking adequate calibration, while ship- and mooring-based observations are spatially limited and have technical shortcomings. However, wind-generated underwater noise can be used to measure wind speed, a method known as Weather Observations Through Ambient Noise (WOTAN). Here, we adapt the WOTAN technique for application to ocean gliders, enabling calibrated wind speed measurements to be combined with contemporaneous oceanographic profiles over extended spatial and temporal scales. We demonstrate the methodology in three glider surveys in the Mediterranean Sea during winter 2012/13. Wind speeds ranged from 2 to 21.5 m s−1, and the relationship to underwater ambient noise measured from the glider was quantified. A two-regime linear model is proposed, which validates a previous linear model for light winds (below 12 m s−1) and identifies a regime change in the noise generation mechanism at higher wind speeds. This proposed model improves on previous work by extending the validated model range to strong winds of up to 21.5 m s−1. The acquisition, data processing, and calibration steps are described. Future applications for glider-based wind speed observations and the development of a global wind speed estimation model are discussed.

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Prawirasasra, Muhammad Saladin, Mirko Mustonen, and Aleksander Klauson. "The Underwater Soundscape at Gulf of Riga Marine-Protected Areas." Journal of Marine Science and Engineering 9, no. 8 (August 23, 2021): 915. http://dx.doi.org/10.3390/jmse9080915.

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Passive acoustic monitoring (PAM) is widely used as an initial step towards an assessment of environmental status. In the present study, underwater ambient sound recordings from two monitoring locations in marine-protected areas (MPAs) of the Gulf of Riga were analysed. Both locations belong to the natural habitat of pinnipeds whose vocalisations were detected and analysed. An increase of vocal activity during the mating period in the late winter was revealed, including percussive signallings of grey seals. The ambient sound spectra showed that in the current shallow sea conditions ship traffic noise contributed more in the higher frequency bands. Thus, a 500 Hz one-third octave band was chosen as an indicator frequency band for anthropogenic noise in the monitoring area. It was shown that changes in the soundscape occurring during the freezing period create favourable conditions for ship noise propagation at larger distances. Based on the monitoring data, the environmental risks related to the anthropogenic sound around the monitoring sites were considered as low. However, further analysis showed that for a small percentage of time the ship traffic can cause auditory masking for the ringed seals.

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Heaney, Kevin D., Christopher Verlinden, Kerri D. Seger, Jennifer Brandon, Leila Hatch, Martha Schönau, and Andrew Heaney. "The Arctic underwater soundscape today and as projected for 2030." Journal of the Acoustical Society of America 151, no. 4 (April 2022): A189. http://dx.doi.org/10.1121/10.0011059.

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Canada, the United States, and the World Wildlife Fund are co-sponsoring ongoing work in the Arctic Council’s Protection for the Marine Environment Working Group to evaluate shipping noise in the Arctic region. Applied Ocean Sciences has used ship tracking and sea ice data to model the region’s underwater soundscape to improve understanding of radiated noise generated by shipping throughout the PanArctic. Current (2019) models have been compared with ambient noise measurements collected during time periods when vessel sounds were identifiably present and when biological sounds were not. Projections of ice cover and shipping routes along and between the northern borders of Arctic countries were used to forecast potential future (2030) Arctic soundscapes. Focused interpretation of these model results within sub-regions, time periods, and frequencies important to marine fauna and in turn to indigenous peoples will be provided to PAME and other fora seeking to guide the development of shipping practices and mitigation strategies. The final results will be incorporated as a PAME/Arctic Council product. This presentation will focus on the acoustic modeling work under projected sea ice conditions, maps of “excess noise” induced by ships in 2019 and 2030, and risk assessment for a few endemic marine mammal species.

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Larsson Nordström, Robin, Emilia Lalander, Isaac Skog, and Mathias Andersson. "Maximum likelihood separation of anthropogenic and wind-generated underwater noise." Journal of the Acoustical Society of America 152, no. 3 (September 2022): 1292–99. http://dx.doi.org/10.1121/10.0013887.

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A method is presented for simultaneous estimation of the probability distributions of both anthropogenic and wind-generated underwater noise power spectral density using only acoustic data recorded with a single hydrophone. Probability density models for both noise sources are suggested, and the model parameters are estimated using the method of maximum likelihood. A generic mixture model is utilized to model a time invariant anthropogenic noise distribution. Wind-generated noise is assumed normally distributed with a wind speed-dependent mean. The mean is then modeled as an affine linear function of the wind-generated noise level at a reference frequency, selected in a frequency range where the anthropogenic noise is less dominant. The method was used to successfully estimate the wind-generated noise spectra from ambient noise recordings collected at two locations in the southern Baltic Sea. At the North location, 3 km from the nearest shipping lane, the ship noise surpasses the wind-generated noise almost 100% of the time in the frequency band 63–400 Hz during summer for wind speed 7 m/s. At the South location, 14 km to the nearest shipping lane, the ship noise dominance is lower but still 40%–90% in the same frequencies and wind speed.

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Zhang, Ying, Kunde Yang, Qiulong Yang, and Cheng Chen. "Mapping sea surface observations to spectra of underwater ambient noise through self-organizing map method." Journal of the Acoustical Society of America 146, no. 2 (August 2019): EL111—EL116. http://dx.doi.org/10.1121/1.5120542.

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Bagočius, Donatas, and Aleksas Narščius. "Simplistic underwater ambient noise modelling for shallow coastal areas: Lithuanian area of the Baltic Sea." Ocean Engineering 164 (September 2018): 521–28. http://dx.doi.org/10.1016/j.oceaneng.2018.06.055.

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Seo, Iksu, Seongweon Kim, Youngwoo Ryu, Jungyong Park, and Dong Seog Han. "Underwater Moving Target Classification Using Multilayer Processing of Active Sonar System." Applied Sciences 9, no. 21 (October 30, 2019): 4617. http://dx.doi.org/10.3390/app9214617.

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The task of detecting and classifying highly maneuverable and unidentified underwater targets in complex environments is significant in active sonar systems. Previous studies have applied many detection schemes to this task using signals above a preset threshold to separate targets from clutter; this is because a high signal-to-noise ratio (SNR) target has sufficient feature vector components to be separated out. However, in real environments, the received target return’s SNR is not always above the threshold. Therefore, a target detection algorithm is needed for varied target SNR conditions. When the clutter energy is too strong, false detection can occur, and the probability of detection is reduced due to the weak target signature. Furthermore, since a long pulse repetition interval is used for long-range detection and ambient noise tends to be high, classification processing for each ping is needed. This paper proposes a multilayer classification algorithm applicable to all signals in real underwater environments above the noise level without thresholding and verifies the algorithm’s classification performance. We obtained a variety of experimental data by using a real underwater target and a hull-mounted active sonar system operated on Korean naval ships in the East Sea, Korea. The detection performance of the proposed algorithm was evaluated in terms of the classification rate and false alarm rate as a function of the SNR. Since experimental environment data, including the sea state, target maneuvering patterns, and sound speed, were available, we selected 1123 instances of ping data from the target over all experiments and randomly selected 1000 clutters based on the distribution of clutters for each ping. A support vector machine was employed as the classifier, and 80% of the data were selected for training, leaving the remaining data for testing. This process was carried out 1000 times. For the performance analysis and discussions, samples of scatter diagrams and feature characteristics are shown and classification tables and receiver operation characteristic (ROC) curves are presented. The results show that the proposed algorithm is effective under a variety of target strengths and ambient noise levels.

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Jeong, Inyong, and Dong-Guk Paeng. "Circadian and Tidal Changes in Snapping Shrimp (Alpheus brevicristatus) Sound Observed by a Moored Hydrophone in the Coastal Sea of Western Jeju." Applied Sciences 12, no. 13 (June 27, 2022): 6493. http://dx.doi.org/10.3390/app12136493.

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Numerous studies have evaluated the acoustic characteristics of soniferous snapping shrimp, but a few are based on long-term mooring measurements. In this study, underwater ambient noise signals were collected from a hydrophone moored 10 m from the sea bed in the coastal sea of western Jeju, South Korea, from mid-September 2019 for 90 days to analyze the variation in the sound of snapping shrimp. The kernel signal and a threshold value were utilized to identify the snapping shrimp, and the snap rate per minute was computed for quantitative analysis. The results show that the mean and standard deviation of the snap rate in the western sea of Jeju was 2132 ± 432 per minute during the whole measurement period. The surface water temperature and tidal level decreased by 7 °C from 25 °C and 50 cm from 190 cm, respectively, over 90 days. The snap rate decreased from September mainly due to the decrease in water temperature by 71 times per minute for every 1 °C decrease. It showed a circadian cycle, increasing by 17~24% at sunrise and sunset compared to the daytime minimum. The snap rate at night was the highest in late summer but the rate dropped like the one during the day in late fall. The snap rate at high tide was 13% higher on average than at low tide. The circadian and tidal changes of the snapping shrimp sound from long-term mooring measurements may be used as primary data for underwater ambient noise and the ecological behavior of snapping shrimp.

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Kim, Byoung-Nam, Bok Kyoung Choi, Seong Hyeon Kim, Bong-Chae Kim, Seom-Kyu Jung, and Yong-Kuk Lee. "Effect of underwater sound channel on variation of ambient noise level in eastern sea of Korea." Japanese Journal of Applied Physics 53, no. 7S (June 23, 2014): 07KG04. http://dx.doi.org/10.7567/jjap.53.07kg04.

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Yang, Qiulong, and Kunde Yang. "Seasonal comparison of underwater ambient noise observed in the deep area of the South China Sea." Applied Acoustics 172 (January 2021): 107672. http://dx.doi.org/10.1016/j.apacoust.2020.107672.

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Yang, Qiulong, Kunde Yang, Shunli Duan, and Yuanliang Ma. "Statistics of underwater ambient noise at high sea states arisen from typhoon out zones in the Philippine Sea and South China Sea." Acta Oceanologica Sinica 41, no. 7 (July 2022): 153–65. http://dx.doi.org/10.1007/s13131-022-1991-7.

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Chen, Rui, Andrew J. Poulsen, and Henrik Schmidt. "Spectral, spatial, and temporal characteristics of underwater ambient noise in the Beaufort Sea in 1994 and 2016." Journal of the Acoustical Society of America 144, no. 3 (September 2018): 1695. http://dx.doi.org/10.1121/1.5067534.

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Chen, R., A. Poulsen, and H. Schmidt. "Spectral, spatial, and temporal characteristics of underwater ambient noise in the Beaufort Sea in 1994 and 2016." Journal of the Acoustical Society of America 145, no. 2 (February 2019): 605–14. http://dx.doi.org/10.1121/1.5088601.

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Ma, Barry B., and Jeffrey A. Nystuen. "Detection of Rainfall Events Using Underwater Passive Aquatic Sensors and Air–Sea Temperature Changes in the Tropical Pacific Ocean." Monthly Weather Review 135, no. 10 (October 1, 2007): 3599–612. http://dx.doi.org/10.1175/mwr3487.1.

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Abstract Several years of long-term high temporal resolution ocean ambient noise data from the tropical Pacific Ocean are analyzed to detect oceanic rainfall. Ocean ambient noise generated by rainfall and wind are identified through an acoustic discrimination process. Once the spectra are classified, wind speed and rainfall rates are quantified using the empirical algorithms. Rainfall-rate time series have temporal resolutions of 1 min. These data provide a unique opportunity to study the rainfall events and patterns in two different climate regions, the intertropical convergence zone (ITCZ) of the tropical eastern Pacific (10° and 12°N, 95°W) and the equatorial western Pacific (0°, 165°E). At both locations the rain events have a mean rainfall of 15 mm h−1, but the events are longer in the eastern Pacific. After the rain event is defined, the probability that a rain event can be detected using the change in air–sea temperature often associated with the rainfall is investigated. The result shows that the rain event accompanied by the decrease of air temperature is a general feature, but that using the temperature difference to detect the rainfall has a very high false alarm rate, which makes it unsuitable for rainfall detection.

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Pensieri, Sara, Roberto Bozzano, Jeffrey A. Nystuen, Emmanouil N. Anagnostou, Marios N. Anagnostou, and Renzo Bechini. "Underwater Acoustic Measurements to Estimate Wind and Rainfall in the Mediterranean Sea." Advances in Meteorology 2015 (2015): 1–18. http://dx.doi.org/10.1155/2015/612512.

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Oceanic ambient noise measurements can be analyzed to obtain qualitative and quantitative information about wind and rainfall phenomena over the ocean filling the existing gap of reliable meteorological observations at sea. The Ligurian Sea Acoustic Experiment was designed to collect long-term synergistic observations from a passive acoustic recorder and surface sensors (i.e., buoy mounted rain gauge and anemometer and weather radar) to support error analysis of rainfall rate and wind speed quantification techniques developed in past studies. The study period included combination of high and low wind and rainfall episodes and two storm events that caused two floods in the vicinity of La Spezia and in the city of Genoa in 2011. The availability of high resolution in situ meteorological data allows improving data processing technique to detect and especially to provide effective estimates of wind and rainfall at sea. Results show a very good correspondence between estimates provided by passive acoustic recorder algorithm and in situ observations for both rainfall and wind phenomena and demonstrate the potential of using measurements provided by passive acoustic instruments in open sea for early warning of approaching coastal storms, which for the Mediterranean coastal areas constitutes one of the main causes of recurrent floods.

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Lee, Seungwoo, Iksu Seo, Jongwon Seok, Yunsu Kim, and Dong Seog Han. "Active Sonar Target Classification with Power-Normalized Cepstral Coefficients and Convolutional Neural Network." Applied Sciences 10, no. 23 (November 26, 2020): 8450. http://dx.doi.org/10.3390/app10238450.

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Detection and classification of unidentified underwater targets maneuvering in complex underwater environments are critical for active sonar systems. In previous studies, many detection methods were applied to separate targets from the clutter using signals that exceed a preset threshold determined by the sonar console operator. This is because the high signal-to-noise ratio target has enough feature vector components to separate. However, in a real environment, the signal-to-noise ratio of the received target does not always exceed the threshold. Therefore, a target detection algorithm for various target signal-to-noise ratio environments is required; strong clutter energy can lead to false detection, while weak target signals reduce the probability of detection. It also uses long pulse repetition intervals for long-range detection and high ambient noise, requiring classification processing for each ping without accumulating pings. In this study, a target classification algorithm is proposed that can be applied to signals in real underwater environments above the noise level without a threshold set by the sonar console operator, and the classification performance of the algorithm is verified. The active sonar for long-range target detection has low-resolution data; thus, feature vector extraction algorithms are required. Feature vectors are extracted from the experimental data using Power-Normalized Cepstral Coefficients for target classification. Feature vectors are also extracted with Mel-Frequency Cepstral Coefficients and compared with the proposed algorithm. A convolutional neural network was employed as the classifier. In addition, the proposed algorithm is to be compared with the result of target classification using a spectrogram and convolutional neural network. Experimental data were obtained using a hull-mounted active sonar system operating on a Korean naval ship in the East Sea of South Korea and a real maneuvering underwater target. From the experimental data with 29 pings, we extracted 361 target and 3351 clutter data. It is difficult to collect real underwater target data from the real sea environment. Therefore, the number of target data was increased using the data augmentation technique. Eighty percent of the data was used for training and the rest was used for testing. Accuracy value curves and classification rate tables are presented for performance analysis and discussion. Results showed that the proposed algorithm has a higher classification rate than Mel-Frequency Cepstral Coefficients without affecting the target classification by the signal level. Additionally, the obtained results showed that target classification is possible within one ping data without any ping accumulation.

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Kshirsagar, Pravin R., Hariprasath Manoharan, S. Shitharth, Abdulrhman M. Alshareef, Dilbag Singh, and Heung-No Lee. "Probabilistic Framework Allocation on Underwater Vehicular Systems Using Hydrophone Sensor Networks." Water 14, no. 8 (April 15, 2022): 1292. http://dx.doi.org/10.3390/w14081292.

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This article emphasis the importance of constructing an underwater vehicle monitoring system to solve various issues that are related to deep sea explorations. For solving the issues, conventional methods are not implemented, whereas a new underwater vehicle is introduced which acts as a sensing device and monitors the ambient noise in the system. However, the fundamentals of creating underwater vehicles have been considered from conventional systems and the new formulations are generated. This innovative sensing device will function based on the energy produced by the solar cells which will operate for a short period of time under the water where low parametric units are installed. In addition, the energy consumed for operating a particular unit is much lesser and this results in achieving high reliability using a probabilistic path finding algorithm. Further, two different application segments have been solved using the proposed formulations including the depth of monitoring the ocean. To validate the efficiency of the proposed method, comparisons have been made with existing methods in terms of navigation output units, rate of decomposition for solar cells, reliability rate, and directivity where the proposed method proves to be more efficient for an average percentile of 64%.

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Patiris, Dionisis L., Sara Pensieri, Christos Tsabaris, Roberto Bozzano, Effrossyni G. Androulakaki, Marios N. Anagnostou, and Stylianos Alexakis. "Rainfall Investigation by Means of Marine In Situ Gamma-ray Spectrometry in Ligurian Sea, Mediterranean Sea, Italy." Journal of Marine Science and Engineering 9, no. 8 (August 21, 2021): 903. http://dx.doi.org/10.3390/jmse9080903.

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Marine in situ gamma-ray spectrometry was utilized for a rainfall study at the W1M3A observing system in Ligurian Sea, Mediterranean Sea, Italy. From 7 June to 10 October 2016, underwater total gamma-ray counting rate (TCR) and the activity concentration of radon daughters 214Pb, 214Bi and potassium 40K were continuously monitored along with ambient noise and meteorological parameters. TCR was proven as a good rainfall indicator as radon daughters’ fallout resulted in increased levels of marine radioactivity during and 2–3 h after the rainfall events. Cloud origin significantly affects TCR and radon progenies variations, as aerial mass trajectories, which extend upon terrestrial areas, result in higher increments. TCR and radon progenies concentrations revealed an increasing non-linear trend with rainfall height and intensity. 40K was proven to be an additional radio-tracer as its dilution was associated with rainfall height. 40K variations combined with 214Bi measurements can be used to investigate the mixing of rain- and seawater. In comparison with measurements in the atmosphere, the application of marine in situ gamma-ray spectrometry for precipitation investigation provided important advantages: allows quantitative measurement of the radionuclides; 40K can be used, along with radon daughters, as a radio-tracer; the mixing of rain- and seawater can be associated with meteorological parameters.

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Parnell, Kirby, Karlina Merkens, Aude Pacini, and Lars Bejder. "Underwater soundscapes at critical habitats of the endangered Hawaiian monk seal." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A291. http://dx.doi.org/10.1121/10.0016317.

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Describing underwater soundscapes of critical habitats of marine mammals can provide valuable information on the acoustic environment utilized by sound-reliant animals. For the endangered Hawaiian monk seal (Neomonachus schauinslandi), whose underwater hearing abilities and vocal communication were recently described, the soundscapes of their aquatic habitats are poorly understood. We measured ambient noise levels and identified acoustic signals that contribute to the underwater soundscape at four critical habitats of the Hawaiian monk seal. We deployed SoundTrap 500HF acoustic recorders, at sites with varying habitat types, and recorded continuously for 179 days. We measured broadband (20–24 000 Hz) and octave-band (31.5, 250, 500, and 16 000 Hz center frequencies) sound pressure levels (SPLs) in hourly intervals at each site. Average hourly broadband SPLs ranged from 107.8–123.4 dB re 1 μPa. Octave-band SPLs confirmed diel patterns associated with biological and anthropogenic sources. We recorded two large-scale geophysical events: Hurricane Douglas (Category 4) and a 6.2 magnitude earthquake which increased the 31.5 Hz octave-band SPL. This study provides the first description of underwater soundscapes at critical habitats of the Hawaiian monk seal across its expansive range. These measurements serve as a baseline for future studies to understand the impact of human activity on underwater soundscapes.

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MacGillivray, Alexander, and Christ de Jong. "A Reference Spectrum Model for Estimating Source Levels of Marine Shipping Based on Automated Identification System Data." Journal of Marine Science and Engineering 9, no. 4 (March 30, 2021): 369. http://dx.doi.org/10.3390/jmse9040369.

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Underwater sound mapping is increasingly being used as a tool for monitoring and managing noise pollution from shipping in the marine environment. Sound maps typically rely on tracking data from the Automated Information System (AIS), but information available from AIS is limited and not easily related to vessel noise emissions. Thus, robust sound mapping tools not only require accurate models for estimating source levels for large numbers of marine vessels, but also an objective assessment of their uncertainties. As part of the Joint Monitoring Programme for Ambient Noise in the North Sea (JOMOPANS) project, a widely used reference spectrum model (RANDI 3.1) was validated against statistics of monopole ship source level measurements from the Vancouver Fraser Port Authority-led Enhancing Cetacean Habitat and Observation (ECHO) Program. These validation comparisons resulted in a new reference spectrum model (the JOMOPANS-ECHO source level model) that retains the power-law dependence on speed and length but incorporates class-specific reference speeds and new spectrum coefficients. The new reference spectrum model calculates the ship source level spectrum, in decidecade bands, as a function of frequency, speed, length, and AIS ship type. The statistical uncertainty (standard deviation of the deviation between model and measurement) in the predicted source level spectra of the new model is estimated to be 6 dB.

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Fang, Yin-Ying, Chi-Fang Chen, and Sheng-Ju Wu. "Feature identification using acoustic signature of Ocean Researcher III (ORIII) of Taiwan." ANZIAM Journal 59 (July 25, 2019): C318—C357. http://dx.doi.org/10.21914/anziamj.v59i0.12655.

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Underwater acoustic signature identification has been employed as a technique for detecting underwater vehicles, such as in anti-submarine warfare or harbour security systems. The underwater sound channel, however, has interference due to spatial variations in topography or sea state conditions and temporal variations in water column properties, which cause multipath and scattering in acoustic propagation. Thus, acoustic data quality control can be very challenging. One of challenges for an identification system is how to recognise the same target signature from measurements under different temporal and spatial settings. This paper deals with the above challenges by establishing an identification system composed of feature extraction, classification algorithms, and feature selection with two approaches to recognise the target signature of underwater radiated noise from a research vessel, Ocean Researcher III, with a bottom mounted hydrophone in five cruises in 2016 and 2017. The fundamental frequency and its power spectral density are known as significant features for classification. In feature extraction, we extract the features before deciding which is more significant from the two aforementioned features. The first approach utilises Polynomial Regression (PR) classifiers and feature selection by Taguchi method and analysis of variance under a different combination of factors and levels. The second approach utilises Radial Basis Function Neural Network (RBFNN) selecting the optimised parameters of classifier via genetic algorithm. The real-time classifier of PR model is robust and superior to the RBFNN model in this paper. This suggests that the Automatic Identification System for Vehicles using Acoustic Signature developed here can be carried out by utilising harmonic frequency features extracted from unmasking the frequency bandwidth for ship noises and proves that feature extraction is appropriate for our targets. References Nathan D Merchant, Kurt M Fristrup, Mark P Johnson, Peter L Tyack, Matthew J Witt, Philippe Blondel, and Susan E Parks. Measuring acoustic habitats. Methods in Ecology and Evolution, 6(3):257265, 2015. doi:10.1111/2041-210X.12330. Nathan D Merchant, Philippe Blondel, D Tom Dakin, and John Dorocicz. Averaging underwater noise levels for environmental assessment of shipping. The Journal of the Acoustical Society of America, 132(4):EL343EL349, 2012. doi:10.1121/1.4754429. Chi-Fang Chen, Hsiang-Chih Chan, Ray-I Chang, Tswen-Yung Tang, Sen Jan, Chau-Chang Wang, Ruey-Chang Wei, Yiing-Jang Yang, Lien-Siang Chou, Tzay-Chyn Shin, et al. Data demonstrations on physical oceanography and underwater acoustics from the marine cable hosted observatory (macho). In OCEANS, 2012-Yeosu, pages 16. IEEE, 2012. doi:10.1109/OCEANS-Yeosu.2012.6263639. Sauda Sadaf P Yashaswini, Soumya Halagur, Fazil Khan, and Shanta Rangaswamy. A literature survey on ambient noise analysis for underwater acoustic signals. International Journal of Computer Engineering and Sciences, 1(7):19, 2015. doi:10.26472/ijces.v1i7.37. Shuguang Wang and Xiangyang Zeng. Robust underwater noise targets classification using auditory inspired time-frequency analysis. Applied Acoustics, 78:6876, 2014. doi:10.1016/j.apacoust.2013.11.003. LG Weiss and TL Dixon. Wavelet-based denoising of underwater acoustic signals. The Journal of the Acoustical Society of America, 101(1):377383, 1997. doi:10.1121/1.417983. Timothy Alexis Bodisco, Jason D'Netto, Neil Kelson, Jasmine Banks, Ross Hayward, and Tony Parker. Characterising an ecg signal using statistical modelling: a feasibility study. ANZIAM Journal, 55:3246, 2014. doi:10.21914/anziamj.v55i0.7818. José Ribeiro-Fonseca and Luís Correia. Identification of underwater acoustic noise. In OCEANS'94.'Oceans Engineering for Today's Technology and Tomorrow's Preservation.'Proceedings, volume 2, pages II/597II/602 vol. 2. IEEE. Linus YS Chiu and Hwei-Ruy Chen. Estimation and reduction of effects of sea surface reflection on underwater vertical channel. In Underwater Technology Symposium (UT), 2013 IEEE International, pages 18. IEEE, 2013. doi:10.1109/UT.2013.6519874. G.M. Wenz. Acoustic ambient noise in the ocean: spectra and sources. Thesis, 1962. doi:10.1121/1.1909155. Donald Ross. Mechanics of underwater noise. Elsevier, 2013. doi:10.1121/1.398685. Chris Drummond and Robert C Holte. Exploiting the cost (in) sensitivity of decision tree splitting criteria. In ICML, volume 1, 2000. Charles Elkan. The foundations of cost-sensitive learning. In International joint conference on artificial intelligence, volume 17, pages 973978. Lawrence Erlbaum Associates Ltd, 2001. Chris Gillard, Alexei Kouzoubov, Simon Lourey, Alice von Trojan, Binh Nguyen, Shane Wood, and Jimmy Wang. Automatic classification of active sonar echoes for improved target identification. Douglas C Montgomery. Design and analysis of experiments. John wiley and sons, 2017. doi:10.1002/9781118147634. G Taguchi. Off-line and on-line quality control systems. In Proceedings of International Conference on Quality Control, 1978. Sheng-Ju Wu, Sheau-Wen Shiah, and Wei-Lung Yu. Parametric analysis of proton exchange membrane fuel cell performance by using the taguchi method and a neural network. Renewable Energy, 34(1):135144, 2009. doi:10.1016/j.renene.2008.03.006. Genichi Taguchi. Introduction to quality engineering: designing quality into products and processes. Technical report, 1986. doi:10.1002/qre.4680040216. Richard Horvath, Gyula Matyasi, and Agota Dregelyi-Kiss. Optimization of machining parameters for fine turning operations based on the response surface method. ANZIAM Journal, 55:250265, 2014. doi:10.21914/anziamj.v55i0.7865. Chuan-Tien Li, Sheng-Ju Wu, and Wei-Lung Yu. Parameter design on the multi-objectives of pem fuel cell stack using an adaptive neuro-fuzzy inference system and genetic algorithms. International Journal of Hydrogen Energy, 39(9):45024515, 2014. doi:10.1016/j.ijhydene.2014.01.034. Antoine Guisan, Thomas C Edwards Jr, and Trevor Hastie. Generalized linear and generalized additive models in studies of species distributions: setting the scene. Ecological modelling, 157(2-3):89100, 2002. doi:10.1016/S0304-3800(02)00204-1. Sheng Chen, Colin FN Cowan, and Peter M Grant. Orthogonal least squares learning algorithm for radial basis function networks. IEEE Transactions on neural networks, 2(2):302309, 1991. doi:10.1109/72.80341. Howard Demuth and Mark Beale. Neural network toolbox for use with matlab-user's guide verion 4.0. 1993. Janice Gaffney, Charles Pearce, and David Green. Binary versus real coding for genetic algorithms: A false dichotomy? ANZIAM Journal, 51:347359, 2010. doi:10.21914/anziamj.v51i0.2776. Daniel May and Muttucumaru Sivakumar. Techniques for predicting total phosphorus in urban stormwater runoff at unmonitored catchments. ANZIAM Journal, 45:296309, 2004. doi:10.21914/anziamj.v45i0.889. Chang-Xue Jack Feng, Zhi-Guang Yu, and Andrew Kusiak. Selection and validation of predictive regression and neural network models based on designed experiments. IIE Transactions, 38(1):1323, 2006. doi:10.1080/07408170500346378. Yin-Ying Fang, Ping-Jung Sung, Kai-An Cheng, Meng Fan Tsai, and Chifang Chen. Underwater radiated noise measurement of ocean researcher 3. In The 29th Taiwan Society of Naval Architects and Marine Engineers Conference, 2017. Yin-Ying Fang, Chi-Fang Chen, and Sheng-Ju Wu. Analysis of vibration and underwater radiated noise of ocean researcher 3. In The 30th Taiwan Society of Naval Architects and Marine Engineers Conference, 2018. Det Norske Veritas. Rules for classification of ships new buildings special equipment and systems additional class part 6 chapter 24 silent class notation. Rules for Classification of ShipsNewbuildings, 2010. Underwater acousticsquantities and procedures for description and measurement of underwater sound from ships-part 1requirements for precision measurements in deep water used for comparison purposes. (ISO 17208-1:2012), 2012. Bureau Veritas. Underwater radiated noise, rule note nr 614 dt r00 e. Bureau Veritas, 2014. R.J. Urick. Principles of underwater sound, volume 3. McGraw-Hill New York, 1983. Lars Burgstahler and Martin Neubauer. New modifications of the exponential moving average algorithm for bandwidth estimation. In Proc. of the 15th ITC Specialist Seminar, 2002. Bishnu Prasad Lamichhane. Removing a mixture of gaussian and impulsive noise using the total variation functional and split bregman iterative method. ANZIAM Journal, 56:5267, 2015. doi:10.21914/anziamj.v56i0.9316. Chao-Ton Su. Quality engineering: off-line methods and applications. CRC press, 2016. Jiju Antony and Mike Kaye. Experimental quality: a strategic approach to achieve and improve quality. Springer Science and Business Media, 2012. Ozkan Kucuk, Tayeb Elfarah, Serkan Islak, and Cihan Ozorak. Optimization by using taguchi method of the production of magnesium-matrix carbide reinforced composites by powder metallurgy method. Metals, 7(9):352, 2017. doi:10.3390/met7090352. G Taguchi. System of experimental design, quality resources. New York, 108, 1987. Gavin C Cawley and Nicola LC Talbot. Efficient leave-one-out cross-validation of kernel fisher discriminant classifiers. Pattern Recognition, 36(11):25852592, 2003. doi:10.1016/S0031-3203(03)00136-5.

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Ma, Barry B., and Jeffrey A. Nystuen. "Passive Acoustic Detection and Measurement of Rainfall at Sea." Journal of Atmospheric and Oceanic Technology 22, no. 8 (August 1, 2005): 1225–48. http://dx.doi.org/10.1175/jtech1773.1.

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Abstract Rainfall over the ocean is one of the most important climatic parameters for both oceanic and atmospheric science. Traditional accumulation-type rain gauges are difficult to operate at sea, and so an alternate technique using underwater sound has been developed. The technique of passive monitoring of the ocean rainfall using ambient sound depends on the accuracy of sound pressure level (SPL) detection. Consequently, absolute calibration of the hydrophone is desirable, but is difficult to achieve because typically the geometry of the laboratory calibration process does not fit the measurement geometry over the ocean. However, if one assumes that the sound signal that is generated by wind is universal then the wind signal can be used to provide an absolute calibration. Over 90 buoy months of ambient sound spectra have been collected on the Tropical Atmosphere Ocean (TAO) project array since 1998. By applying the Vagle et al. wind speed algorithm, the instrument noises and sensitivity bias for the absolute calibration of each acoustic rain gauge (ARG) are obtained. An acoustic discrimination process is developed to retrieve the pure geophysical signals. A new single-frequency rainfall-rate algorithm is proposed after comparing the ARG data with R.M. Young self-siphoning rain gauge data, collocated on the same moorings. The acoustic discrimination process and the rainfall algorithm are further tested at two other locations and are compared with R.M. Young rain gauges and the Tropical Rain Measuring Mission (TRMM) product 3B42. The acoustic rainfall accumulations show the comparable results in both long (year) and short (hours) time scales.

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Thums, Michele, Scott D. Whiting, Julia Reisser, Kellie L. Pendoley, Charitha B. Pattiaratchi, Maira Proietti, Yasha Hetzel, Rebecca Fisher, and Mark G. Meekan. "Artificial light on water attracts turtle hatchlings during their near shore transit." Royal Society Open Science 3, no. 5 (May 2016): 160142. http://dx.doi.org/10.1098/rsos.160142.

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We examined the effect of artificial light on the near shore trajectories of turtle hatchlings dispersing from natal beaches. Green turtle ( Chelonia mydas ) hatchlings were tagged with miniature acoustic transmitters and their movements tracked within an underwater array of 36 acoustic receivers placed in the near shore zone. A total of 40 hatchlings were tracked, 20 of which were subjected to artificial light during their transit of the array. At the same time, we measured current speed and direction, which were highly variable within and between experimental nights and treatments. Artificial lighting affected hatchling behaviour, with 88% of individual trajectories oriented towards the light and spending, on average, 23% more time in the 2.25 ha tracking array (19.5 ± 5 min) than under ambient light conditions (15.8 ± 5 min). Current speed had little to no effect on the bearing (angular direction) of the hatchling tracks when artificial light was present, but under ambient conditions it influenced the bearing of the tracks when current direction was offshore and above speeds of approximately 32.5 cm s −1 . This is the first experimental evidence that wild turtle hatchlings are attracted to artificial light after entering the ocean, a behaviour that is likely to subject them to greater risk of predation. The experimental protocol described in this study can be used to assess the effect of anthropogenic (light pollution, noise, etc.) and natural (wave action, current, wind, moonlight) influences on the in-water movements of sea turtle hatchlings during the early phase of dispersal.

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La Manna, Gabriella, Marta Picciulin, Alessia Crobu, Francesco Perretti, Fabio Ronchetti, Michele Manghi, Alberto Ruiu, and Giulia Ceccherelli. "Marine soundscape and fish biophony of a Mediterranean marine protected area." PeerJ 9 (December 15, 2021): e12551. http://dx.doi.org/10.7717/peerj.12551.

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Background Marine soundscape is the aggregation of sound sources known as geophony, biophony, and anthrophony. The soundscape analysis, in terms of collection and analysis of acoustic signals, has been proposed as a tool to evaluate the specific features of ecological assemblages and to estimate their acoustic variability over space and time. This study aimed to characterise the Capo Caccia-Isola Piana Marine Protected Area (Italy, Western Mediterranean Sea) soundscape over short temporal (few days) and spatial scales (few km) and to quantify the main anthropogenic and biological components, with a focus on fish biophonies. Methods Within the MPA, three sites were chosen each in a different protection zone (A for the integral protection, B as the partial protection, and C as the general protection). In each site, two underwater autonomous acoustic recorders were deployed in July 2020 at a depth of about 10 m on rocky bottoms. To characterise the contribution of both biophonies and anthrophonies, sea ambient noise (SAN) levels were measured as sound pressure level (SPL dB re: 1 μ Pa-rms) at eight 1/3 octave bands, centred from 125 Hz to 16 kHz, and biological and anthropogenic sounds were noted. Fish sounds were classified and counted following a catalogue of known fish sounds from the Mediterranean Sea based on the acoustic characteristic of sound types. A contemporary fish visual census had been carried out at the test sites. Results SPL were different by site, time (day vs. night), and hour. SPLs bands centred at 125, 250, and 500 Hz were significantly higher in the daytime, due to the high number of boats per minute whose noise dominated the soundscapes. The loudest man-made noise was found in the A zone, followed by the B and the C zone, confirming that MPA current regulations do not provide protection from acoustic pollution. The dominant biological components of the MPA soundscape were the impulsive sounds generated by some invertebrates, snapping shrimps and fish. The vast majority of fish sounds were recorded at the MPA site characterized by the highest sound richness, abundance, and Shannon-Wiener index, coherently with the results of a fish visual census. Moreover, the acoustic monitoring detected a sound associated with a cryptic species (Ophidion spp.) never reported in the study area before, further demonstrating the usefulness of passive acoustic monitoring as a complementary technique to species census. This study provides baseline data to detect future changes of the marine soundscapes and some suggestions to reduce the impact of noise on marine biodiversity.

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Dahl, Peter H., James H. Miller, Douglas H. Cato, and Rex K. Andrew. "Underwater Ambient Noise." Acoustics Today 3, no. 1 (2007): 23. http://dx.doi.org/10.1121/1.2961145.

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Nystuen, Jeffrey A. "Rainfall measurements using underwater ambient noise." Journal of the Acoustical Society of America 79, no. 4 (April 1986): 972–82. http://dx.doi.org/10.1121/1.393695.

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Quijano, Jorge E., Stan E. Dosso, Martin Siderius, and Lanfranco Muzi. "Coherence extrapolation for underwater ambient noise." Journal of the Acoustical Society of America 135, no. 6 (June 2014): EL318—EL323. http://dx.doi.org/10.1121/1.4879663.

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Snyder, Mark A., Pete Orlin, Annette Schulte, and Joal Newcomb. "Ambient noise analysis of underwater acoustic data." Journal of the Acoustical Society of America 113, no. 4 (April 2003): 2320. http://dx.doi.org/10.1121/1.4780783.

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Urick, Robert, and W. A. Kuperman. "Ambient Noise in the Sea." Journal of the Acoustical Society of America 86, no. 4 (October 1989): 1626. http://dx.doi.org/10.1121/1.398683.

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Hutt, Daniel L., Andrew L. Rosenfeld, and Paul C. Hines. "Monte Carlo model for underwater ambient noise fields." Journal of the Acoustical Society of America 108, no. 5 (November 2000): 2563. http://dx.doi.org/10.1121/1.4743522.

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Chandrayadula, Tarun K., Chris W. Miller, and John E. Joseph. "Monterey Bay ambient noise profiles using underwater gliders." Journal of the Acoustical Society of America 133, no. 5 (May 2013): 3395. http://dx.doi.org/10.1121/1.4805896.

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Cavanagh, Raymond C. "Bob Urick and ambient sea noise." Journal of the Acoustical Society of America 106, no. 4 (October 1999): 2186. http://dx.doi.org/10.1121/1.427409.

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He, Li, ZhengLin Li, and ZhaoHui Peng. "Ambient noise near the sea-route." Science in China Series G: Physics, Mechanics and Astronomy 52, no. 1 (January 2009): 40–45. http://dx.doi.org/10.1007/s11433-009-0005-5.

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Ashokan, Muthuraj, Ganesan Latha, and Ayyadurai Thirunavukkarasu. "Underwater Ambient Noise in Kongsfjorden, Spitsbergen, during the Summers of 2015 and 2016." ARCTIC 73, no. 3 (September 28, 2020): 386–92. http://dx.doi.org/10.14430/arctic70499.

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Underwater ambient noise was measured in Kongsfjorden, Svalbard, during the summers of 2015 and 2016 to understand the contribution of iceberg bubbling, iceberg calving, and shipping noise to the acoustic environment of the fjord. Comparison of the ambient noise data for the months of August, September, and October showed that average noise levels were similar, although the average noise level for 2015 was ~9 dB higher than in 2016 because of higher shipping noise. Maximum ambient noise was produced at frequencies less than 10 kHz during both summers. Spectrograms of iceberg calving noise showed that it occurred in the frequency below 500 Hz. Shipping noise was seen in the band below 600 Hz, and iceberg bubbling noise was detected in the band above 400 Hz. Instrument noise was observed in the frequency 400 Hz. It is clear that ice breaking and shipping contribute substantially to ambient noise in Kongsfjorden.

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Shchurov, V. A. "Coherent and diffusive fields of underwater acoustic ambient noise." Journal of the Acoustical Society of America 90, no. 2 (August 1991): 991–1001. http://dx.doi.org/10.1121/1.401913.

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Wang, Jing-Yan, and Feng-Hua Li. "Preliminary Study on Underwater Ambient Noise Generated by Typhoons." Chinese Physics Letters 32, no. 4 (April 2015): 044301. http://dx.doi.org/10.1088/0256-307x/32/4/044301.

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Journal articles on the topic 'Underwater sea ambient noise'

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