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Underwater ambient noise on the Chukchi Sea continental slope from 2006–2009
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10.1121/1.3664096
/content/asa/journal/jasa/131/1/10.1121/1.3664096
http://aip.metastore.ingenta.com/content/asa/journal/jasa/131/1/10.1121/1.3664096

Figures

Image of FIG. 1.
FIG. 1.

Location of the HARP site (72° 27.5′ N, 157° 23.4′ W, 235 m depth) along the continental slope, north of Barrow, Alaska. The study site is near the border between the Chukchi and Beaufort Seas. Bathymetric contours are in meters.

Image of FIG. 2.
FIG. 2.

Mean monthly sound spectum levels from September 2006 to May 2007. Each monthly average is based on 200-s samples, selected when no transient signals are present.

Image of FIG. 3.
FIG. 3.

Sound spectrum levels for the months of (a) September 2008, (b) March 2009, and (c) May 2009. Distributions are represented by the mean, 99th, 90th, 50th (median), 10th, and 1st percentiles. Distributions are long-tailed for higher values, with mean values greater than the median.

Image of FIG. 4.
FIG. 4.

Sound spectrum level cumulative distribution functions for the months of September 2008, March 2009, and May 2009 at (a) 50 Hz and (b) 500 Hz. The skewness and excess kurtosis are calculated for each month (inset).

Image of FIG. 5.
FIG. 5.

(a) Time series of mean sound-pressure spectrum levels at 100 Hz, (b) three-day averaged wind speed values from the weather station in Barrow, Alaska, and (c) the percentage of sea ice cover from AMSR-E for a 100 nm radius centered on the instrument site. Shaded periods of time show correlations between significant ambient noise and weather events.

Image of FIG. 6.
FIG. 6.

(a) Two-day averaged sound spectrum levels at 250 Hz versus mean wind speed from September 2006 to June 2009. The “[circo]” represents sound spectrum levels during 0%–25% ice cover (IC), while the “x” represents sound spectrum levels during 75%–100% ice cover. Log transforms are fitted to each data set to estimate the dependence of ambient noise on wind. (b) An analysis of variance for the two surface conditions shows that the two groups of data are distinct from one another and the resulting p-value is small.

Image of FIG. 7.
FIG. 7.

Long-term spectrogram of noise during 16 September to 7 October 2007. Airgun bouts appear with sharp temporal boundaries. Lower bars show timeline of airgun categorization by manual inspection of the time-series data as strong, weak, or none—periods without airguns.

Image of FIG. 8.
FIG. 8.

Sound spectrum levels for the periods of airgun usage shown in Fig. 7 , categorized as either strong, weak, or none.

Image of FIG. 9.
FIG. 9.

Modal dispersion of two airgun shots, received by the hydrophone at 10 m above the seafloor. The shots—20 s apart—each contain four modes observed as frequency upsweeps. The modes are spread-out over more than 5 s with energy between 7 and 80 Hz.

Tables

Generic image for table
TABLE I.

Airgun surveys detected and permitted/reported during 2006–2008 in the Chukchi and Beaufort Seas.

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/content/asa/journal/jasa/131/1/10.1121/1.3664096
2012-01-13
2014-04-16
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Underwater ambient noise on the Chukchi Sea continental slope from 2006–2009
http://aip.metastore.ingenta.com/content/asa/journal/jasa/131/1/10.1121/1.3664096
10.1121/1.3664096
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