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The contribution of bubbles to high-frequency sea surface backscatter: a 24-h time series of field measurements.

Authors
Type
Published Article
Journal
The Journal of the Acoustical Society of America
0001-4966
Publisher
Acoustical Society of America
Publication Date
Volume
113
Issue
2
Pages
769–780
Identifiers
PMID: 12597172
Source
Medline
License
Unknown

Abstract

Measurements of acoustic sea surface backscattering, wind speed, and surface wave spectra were made continually over a 24-h period in an experiment conducted in 26 m of water near the Dry Tortugus collection of islands off south Florida in February 1995. The backscattering measurements were made at a frequency of 30 kHz and a sea surface grazing angle of 20 degrees; a time series of the decibel equivalent of this variable, called SS20, was studied in terms of its dependence on environmental variables. On occasion reliable estimates of scattering in the grazing range 15 degrees-27 degrees were also obtained during the 24 hours. The scattering data exhibited evidence, in terms of scattering level and grazing angle dependence, of scattering from near-surface bubbles rather than scattering from the rough air-sea interface. The scattering data were compared with a model for sigma(b), the apparent backscattering cross section per unit area due to bubble scattering, that is driven by a parameter, beta1, equal to the depth-integrated extinction cross section per unit volume. Using an empirical model for beta1 based on data from a 1977 experiment conducted in pelagic waters, model predictions agreed reasonably well with the 1995 measurements presented here. Additional model-data comparisons were made using four measurements from a 1992 experiment conducted in pelagic waters. Finally, the 24-h time series of acoustic scattering exhibited a hysteresis effect, wherein for a given wind speed, there was a tendency for the scattering level to be higher if prior winds had been falling. A better understanding of this effect is essential to reduce uncertainty in model predictions.

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