Measured and modeled acoustic propagation underneath the rough Arctic sea-ice

Hope, Gaute; Sagen, Hanne; Storheim, Espen; Hobæk, Halvor; Freitag, Lee

doi:10.1121/1.5003786

Cited by 35 publications

(13 citation statements)

References 37 publications

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“…In September 2013, an acoustic propagation experiment UNDER‐ICE was carried out in Fram Strait (marked in Figure 11a) as part of the Waves‐in‐Ice Forecasting for Arctic Operators project (Geyer et al., 2016; Hope et al., 2017). In this experiment, an acoustic source was located 90 m below the surface.…”

Section: Application Of the Acoustic Modelingmentioning

confidence: 99%

An Ocean Acoustic Modeling Based on the Physical Parameters Clustering of the Arctic Ice Floes: Applied to the Study of Acoustic Field Response as Ice Floes Thickness Varies

Zhang

et al. 2023

J Adv Model Earth Syst

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The Arctic region is undergoing drastic environmental change. In recent studies (Nuttall, 2018;Richter-Menge et al., 2018), this area is warming at more than twice the global average due to the Arctic amplification effect. Most human activities in the Arctic Ocean require knowledge of the ocean environment. According to the research of Timmermans and Marshall (2020), complex ocean currents and drifting ice floes at high latitudes are major environmental features of the Arctic Ocean. Wang et al. have already researched ocean current-dependent acoustic propagation modeling (Wang et al., 2021). However, the ice floes-dependent acoustic propagation modeling has not been solved. Applying the drifting ice floes to the acoustic propagation modeling will forward the Arctic Ocean oil exploration, fishery survey, mineral extraction, shipping planning and tourism (Worcester et al., 2020).Arctic ice floes have a general structure and a microstructure (Thomas & Dieckmann, 2010). The general structure contains the physical parameters describing the form of ice floes, such as ice concentration and thickness. The microstructure contains physical parameters describing the interior of ice floes like temperature, salinity, and density. Scientists have done much work on the general structure. Some scholars proposed the earliest sea ice model for acoustic and described the sea ice as semi-elliptical protrusions on a randomly distributed free or rigid base surface (Burke & Twersky, 1966;Diachok, 1976). To verify the Burke model, Yang measured sonic reflectivity below 1 kHz and found the sea ice could be seen as a smooth homogeneous medium (Yang & Votaw, 1981). In 1992, based on the Biot theory, Rajan also suggested that sea ice could be treated as a brine-saturated porous

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Section: Application Of the Acoustic Modelingmentioning

confidence: 99%

An Ocean Acoustic Modeling Based on the Physical Parameters Clustering of the Arctic Ice Floes: Applied to the Study of Acoustic Field Response as Ice Floes Thickness Varies

Zhang

et al. 2023

J Adv Model Earth Syst

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“…This model was able to account for scattering at the icewater interface and the conversion of compressional energy to shear energy, but only for range-independent problems. This model has provided accurate predictions of arrival times for recent tomography measurements in the Fram Strait (Hope et al 2017). Gavrilov and Mikhalevsky (2006) used a normal mode propagation code to demonstrate that the ACOUS tomographic signals likely contained information on the ice thickness, though the range-dependent environment added uncertainty to the result.…”

Section: Modellingmentioning

confidence: 99%

Ambient Noise in the Canadian Arctic

Cook

Barclay

Richards

2020

Springer Polar Sciences

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Numerous studies of ocean ambient noise and under-ice acoustic propagation and reverberation in the Canadian Arctic have been carried out since the 1960s. These studies, largely led by scientists at the Defence Research Establishment Pacific and Defence Research and Development Canada, have been motivated by the need to improve sonar performance prediction in the Arctic over the wide range of seasonal ice, oceanographic, and meteorological conditions at high latitudes. Aside from the valuable insight into the physics of noise generation by sea ice and sound propagation under sea ice, they provide a historical baseline for Arctic ambient noise against which modern measurements can be compared. In 2017, the Department of Fisheries and Oceans added passive acoustic monitoring to their Barrow Strait Real Time Observatory, reporting power spectral density over the acoustic band of 10

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“…The sound speed profile shown in Figure 2 ) , with ρ ice = 0.9 kg/dm 3( [11] ) . The sound speed model and choice of elastic parameters is based on the model described in Hope et al [5]. For the Fram Strait area in early autumn a mean ice-thickness of 2 m would be more realistic [3], but this would lead to almost total reflection at the ice interface [4,5] for this source depth, and a ice thickness of 10 m is used here to better illustrate how the sound interacts with the ice.…”

Section: Full Wavefield Simulation Of Under-ice Propagationmentioning

confidence: 99%

“…The sound speed model and choice of elastic parameters is based on the model described in Hope et al [5]. For the Fram Strait area in early autumn a mean ice-thickness of 2 m would be more realistic [3], but this would lead to almost total reflection at the ice interface [4,5] for this source depth, and a ice thickness of 10 m is used here to better illustrate how the sound interacts with the ice. The sea-floor is a partially reflecting interface at 2000 m, with c p = 2500 m/s, c s = 1500 m/s, α p = α s = 0.5 dB / Λ, and ρ = 2.9 kg / dm 3 .…”

Section: Full Wavefield Simulation Of Under-ice Propagationmentioning

confidence: 99%

A parallelization of the wavenumber integration acoustic modelling package OASES

Hope¹,

Schmidt

2019

Comput Geosci

Self Cite

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The wavenumber integration seismo-elastic model OASES can simulate the wave propagation in layered media, consisting of rough interfaces, elastic and porous layers. Range-dependence is achieved by coupling vertical sections of layers, or cuts, together using the spectral super-element method. Only the specific frequencies, receiver depths, and offsets of interest need to be calculated when using the wavenumber integration technique. However, as pulse propagation at higher frequencies is simulated, denser sampling of frequencies must be used. For complex media with many layers, and many vertical sections, the computation time quickly escalates. By exploiting that each frequency response can be calculated independently, a parallelization of the OASES package has been implemented and is presented here. This makes otherwise computationally unfeasible or unpractical simulations feasible. In this work the parallel OASES package is applied to, and benchmarked on, several acoustic and seismic problems. The increased computation capacity is used to simulate and image the full wave field of several cases, reducing the computation time in one of the cases from 1.5 years to 5 hours.

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Measured and modeled acoustic propagation underneath the rough Arctic sea-ice

Cited by 35 publications

References 37 publications

An Ocean Acoustic Modeling Based on the Physical Parameters Clustering of the Arctic Ice Floes: Applied to the Study of Acoustic Field Response as Ice Floes Thickness Varies

An Ocean Acoustic Modeling Based on the Physical Parameters Clustering of the Arctic Ice Floes: Applied to the Study of Acoustic Field Response as Ice Floes Thickness Varies

Ambient Noise in the Canadian Arctic

A parallelization of the wavenumber integration acoustic modelling package OASES

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