Deep ocean sound speed characteristics passively derived from the ambient acoustic noise field

Abstract

S U M M A R YThe propagation of acoustic waves in the ocean strongly depends on the temperature. Lowfrequency acoustic waves can penetrate the ocean down to depths where few in situ measurements are available. It is therefore attractive to obtain a measure of the deep ocean temperature from acoustic waves. The latter is especially true if the ambient acoustic noise field can be used instead of deterministic transient signals. In this study the acoustic velocity, and hence the temperature, is derived in an interferometric approach from hydrophone array recordings. The arrays were separated by over 125 km, near Ascension Island in the Atlantic Ocean, at a depth of 850 m. Furthermore, the dispersive characteristics of the deep ocean sound channel are resolved based on the retrieved lag times for different modes. In addition, it is shown how the resolution of the interferometric approach can be increased by cross correlating array beams rather than recordings from single-sensor pairs. The observed acoustic lag times between the arrays corresponds well to modelled values, based on full-wave modelling through best-known oceanic models.

A study on the ambient noise field at a hydroacoustic array near Robinson Crusoe Island

“…This lag time error can be estimated from a particular non-isotropic distribution of recorded wave intensity (Froment et al 2010). Recent studies by Woolfe et al (2015) and Evers et al (2017) are probably affected by similar uncertainties, however, the relative errors are much smaller due to the much longer lengthscale, with intersensor distances greater than 100 km. The concept of thermometry, even for such small receiver distances, can be improved by retrieving stationary lag times of multiple sources (Snieder et al 2007).…”

“…The aforementioned sources confine the dominant sources of the hydroacoustic network's ambient noise field. Recent studies have shown the potential of passive hydroacoustic thermometry in the SOFAR channel using traveltime variations of ridge earthquakes (Evers & Snellen 2015) and by crosscorrelating ambient signals recorded at two distinct IMS arrays, H10N and H10S, located near Ascension Island in the South Atlantic Ocean (Woolfe et al 2015;Evers et al 2017).…”

“…Both arrays consist of three hydrophones (H03N1-N3 and H03S1-S3) with an intersensor distance of 2 km (Dahlman et al 2009). Previous studies by Woolfe et al (2015) and Evers et al (2017) applied cross-correlation (CC) algorithms to interarray receiver pairs, between array elements of the north and south arrays at Ascension Island (H10) and Wake Island (H11), yielding an intersensor distance of more than 100 km. Furthermore, Evers et al (2017) applied cross-beam correlation techniques, cross-correlating the array beams retrieved by array processing.…”

“…Previous studies by Woolfe et al (2015) and Evers et al (2017) applied cross-correlation (CC) algorithms to interarray receiver pairs, between array elements of the north and south arrays at Ascension Island (H10) and Wake Island (H11), yielding an intersensor distance of more than 100 km. Furthermore, Evers et al (2017) applied cross-beam correlation techniques, cross-correlating the array beams retrieved by array processing. Interarray cross-correlation at H03 is not possible due to blocking by Robinson Crusoe Island.…”

Hydroacoustic Travel Time Variations as a Proxy for Passive Deep‐Ocean Thermometry—A Cookbook

“…Furthermore, the studies of Evers et al. (2017) and Takagi et al. (2015) indicate the presence of repetitive electronic noise of the H10 data loggers causing spurious coherent cross‐correlations.…”