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Joseph Park, Robert Heitsenrether, and William Sweet

the National Water Level Observation Network (NWLON), a network of more than 200 long-term, continuously operating water level stations around the United States, including island possessions, territories, and the Great Lakes ( ). Since the early 1990s, the primary water level measurement system at most NWLON stations has been an acoustic time-of-flight range sensor encased in a protective well ( Edwing 1991 ). From a logistical perspective, installation and

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Kevin Rogers and Anthony Finn

information on the representativeness of point measurements and the homogeneity of other point observations ( Wilson and Thomson 1994 ). Surveys of recent progress in the field of acoustic tomography of the atmosphere are contained in Jovanović (2008) and Ostashev et al. (2008) . The measurement technique employed here compares the acoustic spectra emitted by an unmanned aerial vehicle (UAV) with the Doppler-shifted spectra received at several ground-based microphones ( Finn and Franklin 2011b ), which

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Anthony Finn and Kevin Rogers

solution has a high importance and typically needs to be strongly deweighted—one may use higher values of p . On the other hand, if we expect a large scatter in the measurements, large errors have a similar impact to small ones, so a lower value of p provides better estimates. 4. Acoustic propagation in simulated atmosphere The principal difficulty in simulating realistic atmospheric profiles lies in the dominance of the nonlinear flow effects and the wide spectrum of scale sizes involved. Sullivan

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Louis Gostiaux and Hans van Haren

1. Introduction Acoustic Doppler current profiler (ADCP) echo intensity data are usually recorded as a by-product of the velocity measurements. Echo intensity reflects the backscattering strength of the water, which is due to the presence of backscatterers such as solid particles, bubbles, or living organisms. The level of echo intensity is also very dependent on the acoustic frequency of the ADCP, because the ratio between the acoustic wavelength and the size of the scatterers partially

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Charlotte E. Wainwright, Phillip M. Stepanian, Phillip B. Chilson, Robert D. Palmer, Evgeni Fedorovich, and Jeremy A. Gibbs

divided into height batches for each range gate for further signal processing. g. Acoustic background noise Acoustic background noise measured by sodars is not easily characterized and contains components due to localized effects, such as traffic, and echoes from nearby stationary objects. Bradley (2012) examined measured noise signals, separating sodar self-noise from external noise, and found that peaks in the measured noise spectrum were of unknown origin, while the external noise between these

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David A. Schecter, Melville E. Nicholls, John Persing, Alfred J. Bedard Jr., and Roger A. Pielke Sr.

amplitude of the infrasound (at 5 km) can exceed the estimated 0.25-Pa threshold only if the characteristic velocity of the turbulence ( V ) is greater than about 40 m s −1 , and if the characteristic length scale is less than a few hundred meters. Although much higher velocity flows at smaller scales would produce notable signals, their existence would be extraordinary in any terrestrial storm system. Let us now briefly turn our attention to field measurements. Acoustic radiation from severe

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Michael C. Gregg and John K. Horne

-dimensional effects due to substantially weakened tail vortices, resulting in a reverse von Kármán vortex street. Flow around the fish is dominantly two-dimensional, and the vortices shed from its tail are nearly vertical when the fish swims horizontally. 3. Acoustic characterization of aggregation backscatter Because tidal currents produce or affect most mixing in shallow water, we surveyed mixing in Monterey Bay by repeating slow, ≈1 m s −1 , transects along survey lines for 12.5 h, the period of the twice

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Stuart Bradley and Sabine von Hünerbein

will be a bias in measured Doppler shift compared to that calculated from simple beam geometry because, for a beam symmetric around the central tilted direction, the angles between wind vector and portions of the beam are not symmetrical about the central direction. Furthermore, there can be bias arising from clipping of the beam by acoustic baffles surrounding the instrument, and these effects are generally difficult to estimate or measure in other ways. Similarly, it is challenging to calculate

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Ann E. Gargett

1. Comment The paper of Greene et al. (2015) revisits a suggestion that acoustic measurements of velocity fields associated with the largest scales of ocean turbulence could be used to estimate a small-scale parameter, the turbulent kinetic energy dissipation rate , through a “large-eddy estimate,” where , , and are typical velocity, time, and length scales of the largest energy-containing eddies of the turbulence ( Gargett 1994 , 1999 ). It is widely accepted ( Pope 2000 ) that these

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Yutaka Yoshikawa and Takahiro Endoh

MSP measurement laborious when estimating long-term averages of the mixing. Acoustic Doppler current profilers (ADCPs) can be used to measure the turbulent Reynolds stress from (high frequency) velocity variances in two different directions ( Lohrmann et al. 1990 ; Lu and Lueck 1999 ; Stacey et al. 1999 ; Rippeth et al. 2003 ). Because this method (the variance method) relies on differences in the velocity variances, measurement errors (noise) included in the variance can easily contaminate the

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