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Figure 6.7 Trends with wind speed
U
10
. a) Mean bubble radius
R
0
(denoted as
R
in the figure);
b) Count rate. Combined data sets of
Figure 6.6
are used. Figure is reproduced from
Manasseh
et al.
(
2006
) © American Meteorological Society. Reprinted with permission
Back to our distribution of
b
T
(
f
)
R
(
f
)
,itisshownin
Figure 6.6
c, and
b
T
(
f
)
R
(
f
)
normalised by the spectral density
P
(
f
)
in
Figure 6.6
d. These distributions exhibit features
similar to those of
b
T
(
f
)
in
Figure 5.27
, including the cumulative effect due to induced
breaking at smaller scales.
Further observations can be made in
Figure 6.6
a with respect to the wind effect on
spectral-breaking strength. The mean bubble size
R
0
(
shows that the largest bubbles
were produced by breakers at the highest wind speeds and the smallest bubbles were
produced under the lightest winds. This is also illustrated in
Figure 6.7
, based on the
bubble-detection technique both for breaking severity and bubble-generation rates. The
increase in average bubble size with wind speed is now clear (
Figure 6.7
a). An increase in
bubble-production rate with wind speed can be seen in
Figure 6.7
b. There is an apparent
ordering of the wind speeds with respect to both the bubble rate and the mean radius, with
quite high correlation.
In summary, higher wind speeds in this Lake George observation generate breaking
events more frequently, and the bubbles at higher wind speeds are larger. We should remem-
ber, again, that
R
0
is a proxy of dimensional energy loss rather than of the dimensionless
severity coefficient
s
of
Section 2.7
.In
Section 6.1
, severity was reduced if mechanically
f
)
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