Chapter 7: APPLICATIONS
where Dis the sound absorption coefficient. According to Medwin and Clay
(1998), the absorption coefficient of sound in the ocean is a strong function
of frequency, ranging from 0.5 dB km
-1 at 1 kHz to 10 dB km
-1 at 40 kHz. It
is much higher in seawater than in freshwater. (The change of D for a small
salinity change at a fixed frequency in the range from 0.1 to 100 kHz can be
approximated as
/
/
S S
D D
'
|'
.)
For acoustic rain estimation, it is important to know the effective
listening area of the hydrophone. Rainfall measurements are needed on
relatively large temporal or spatial scales, because rainfall is
inhomogeneous. Larger inherent sampling area should produce better mean
rainfall statistics. The sound spectrum of any single raindrop is variable in
spectral character (except for small raindrops). The inversion techniques
aimed at determination of rain parameters from its acoustic signature are
based on the mean spectrum. It is therefore important to integrate over many
discrete events (individual splashes) to obtain a smooth mean spectrum.
Equation (7.12) can provide an estimate for the effective listening area.
Nystuen (2000) concluded from the analysis of (7.12) that for a uniform
source of sound on the ocean surface (and absorption neglected), 50% of the
sound energy arrives from an area equal to
2
h
S over the hydrophone, while
90% of the sound energy arrives from an area equal to
2
3h
S
, where h is
the depth of the hydrophone.
7.4.7 Passive acoustic monitoring of sea surface processes
Several air-sea interaction processes are responsible for the production
and modification of underwater sound in the ocean as discussed in the
previous section. Passive monitoring of the underwater sound field thus
offers a means to make measurements of these processes. In particular,
breaking wind waves and precipitation are the natural sources of underwater
sound in the frequency range from 500 Hz to 50 kHz. Unique spectral
characteristics of these sound sources allow them to be identified and then
quantified (Nystuen, 2001). Distortion of these acoustic signals by subsurface ambient bubbles in principle permits the detection and quantification
of the near-surface bubbles, which are a potential indicator of the gas
transfer velocity and sea state condition.
Since the resonant frequency depends on the bubble radius, it is
important to know the bubble size distribution and its dependence on depth
and environmental conditions, especially on surface wave parameters. The
surface wave characteristics depend on several factors including wind speed
and its history, fetch etc. For the interpretation of acoustical data, it is
important to know the spectral and other statistical characteristics of surface
waves. The dissipation of wave energy into turbulence appears to be a
473
where Dis the sound absorption coefficient. According to Medwin and Clay
(1998), the absorption coefficient of sound in the ocean is a strong function
of frequency, ranging from 0.5 dB km
-1 at 1 kHz to 10 dB km
-1 at 40 kHz. It
is much higher in seawater than in freshwater. (The change of D for a small
salinity change at a fixed frequency in the range from 0.1 to 100 kHz can be
approximated as
/
/
S S
D D
'
|'
.)
For acoustic rain estimation, it is important to know the effective
listening area of the hydrophone. Rainfall measurements are needed on
relatively large temporal or spatial scales, because rainfall is
inhomogeneous. Larger inherent sampling area should produce better mean
rainfall statistics. The sound spectrum of any single raindrop is variable in
spectral character (except for small raindrops). The inversion techniques
aimed at determination of rain parameters from its acoustic signature are
based on the mean spectrum. It is therefore important to integrate over many
discrete events (individual splashes) to obtain a smooth mean spectrum.
Equation (7.12) can provide an estimate for the effective listening area.
Nystuen (2000) concluded from the analysis of (7.12) that for a uniform
source of sound on the ocean surface (and absorption neglected), 50% of the
sound energy arrives from an area equal to
2
h
S over the hydrophone, while
90% of the sound energy arrives from an area equal to
2
3h
S
, where h is
the depth of the hydrophone.
7.4.7 Passive acoustic monitoring of sea surface processes
Several air-sea interaction processes are responsible for the production
and modification of underwater sound in the ocean as discussed in the
previous section. Passive monitoring of the underwater sound field thus
offers a means to make measurements of these processes. In particular,
breaking wind waves and precipitation are the natural sources of underwater
sound in the frequency range from 500 Hz to 50 kHz. Unique spectral
characteristics of these sound sources allow them to be identified and then
quantified (Nystuen, 2001). Distortion of these acoustic signals by subsurface ambient bubbles in principle permits the detection and quantification
of the near-surface bubbles, which are a potential indicator of the gas
transfer velocity and sea state condition.
Since the resonant frequency depends on the bubble radius, it is
important to know the bubble size distribution and its dependence on depth
and environmental conditions, especially on surface wave parameters. The
surface wave characteristics depend on several factors including wind speed
and its history, fetch etc. For the interpretation of acoustical data, it is
important to know the spectral and other statistical characteristics of surface
waves. The dissipation of wave energy into turbulence appears to be a
473