Temporal and spatial dependence of a yearlong record of sound propagation from the Canada Basin to the Chukchi Shelf.

https://arctichealth.org/en/permalink/ahliterature304683
Source
J Acoust Soc Am. 2020 09; 148(3):1663
Publication Type
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Date
09-2020
Author
Megan S Ballard
Mohsen Badiey
Jason D Sagers
John A Colosi
Altan Turgut
Sean Pecknold
Ying-Tsong Lin
Andrey Proshutinsky
Richard Krishfield
Peter F Worcester
Matthew A Dzieciuch
Author Affiliation
Applied Research Laboratories, The University of Texas at Austin, Austin, Texas 78713, USA.
Source
J Acoust Soc Am. 2020 09; 148(3):1663
Date
09-2020
Language
English
Publication Type
Journal Article
Research Support, U.S. Gov't, Non-P.H.S.
Abstract
The Pacific Arctic Region has experienced decadal changes in atmospheric conditions, seasonal sea-ice coverage, and thermohaline structure that have consequences for underwater sound propagation. To better understand Arctic acoustics, a set of experiments known as the deep-water Canada Basin acoustic propagation experiment and the shallow-water Canada Basin acoustic propagation experiment was conducted in the Canada Basin and on the Chukchi Shelf from summer 2016 to summer 2017. During the experiments, low-frequency signals from five tomographic sources located in the deep basin were recorded by an array of hydrophones located on the shelf. Over the course of the yearlong experiment, the surface conditions transitioned from completely open water to fully ice-covered. The propagation conditions in the deep basin were dominated by a subsurface duct; however, over the slope and shelf, the duct was seen to significantly weaken during the winter and spring. The combination of these surface and subsurface conditions led to changes in the received level of the sources that exceeded 60 dB and showed a distinct spacio-temporal dependence, which was correlated with the locations of the sources in the basin. This paper seeks to quantify the observed variability in the received signals through propagation modeling using spatially sparse environmental measurements.
PubMed ID
33003894 View in PubMed
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