A new tow-yo instrument to observe high-resolution coastal phenomena

Masunaga, Eiji; Yamazaki, Hidekatsu

doi:10.1016/j.jmarsys.2013.09.005

Cited by 30 publications

(14 citation statements)

References 45 publications

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“…We carried out field surveys in Otsuchi Bay, Japan (Figure ) on 10 September 2013. Two types of tow‐yo instruments were deployed for transect observations, namely, the YODA Profiler [ Masunaga and Yamazaki , ] and the Underway CTD (UCTD) [ Rudnick and Klinke , ]. Observations were obtained from 5 m to 120 m depth over a distance of approximately 12 km.…”

Section: Observationsmentioning

confidence: 99%

“…The rate of turbulent kinetic energy dissipation from TurboMAP‐L was estimated with the isotropic formula

ε = 7.5 ν \overset{{((), \frac{d u'}{d z})}^{2}}{true},

where u ′ is the horizontal component of turbulent velocity from a shear probe and ν is the kinematic viscosity of water. The rate of turbulent kinetic energy dissipation is also inferred using a statistical method described in Masunaga and Yamazaki []. To infer the dissipation rate from the YODA Profiler, ε C , we assumed the dissipation rate followed

ε_{C} = a {[\overset{{((), normald C true/ normald z)}^{2}}{true}]}^{b},

Section: Observationsmentioning

confidence: 99%

“…To infer the dissipation rate from the YODA Profiler, ε C , we assumed the dissipation rate followed

ε_{C} = a {[\overset{{((), normald C true/ normald z)}^{2}}{true}]}^{b},

where the coefficients a = 6.5 × 10 −7 and b = 1.26 were obtained with a QQ plot (quantile versus quantile) comparing probability density functions of ε from TurboMAP‐L and the variance of d C /d z from the YODA Profiler. Although this estimation method is an indirect turbulent measurement, the dissipation rate gives a reasonable approximation, at least to the correct order of magnitude [ Masunaga and Yamazaki , ; Masunaga et al ., ].…”

Section: Observationsmentioning

confidence: 99%

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Strong turbulent mixing induced by internal bores interacting with internal tide‐driven vertically sheared flow

Masunaga

Fringer

Yamazaki

et al. 2016

Geophysical Research Letters

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We observed the formation of an internal bore interacting with the vertically sheared flow generated during the previous phase of the internal tide, which resulted in strong turbulent mixing. The rate of turbulent kinetic energy dissipation reached on the order of 10−5 W kg−1 during the event. Numerical simulations reproduced the observed interaction of internal bores with the sheared flow and verified the hypothesized breaking and mixing mechanism. The numerical results indicated that the Iribarren number, or the ratio of the topographic slope to the internal wave slope, plays a major role in the mixing intensity and types of internal bores. It was found that waves with low Iribarren numbers lead to bores that interact with vertically sheared flows induced by the previous phase of the internal tide and are more likely to produce strong wave breaking and mixing.

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Section: Observationsmentioning

confidence: 99%

“…The rate of turbulent kinetic energy dissipation from TurboMAP‐L was estimated with the isotropic formula

ε = 7.5 ν \overset{{((), \frac{d u'}{d z})}^{2}}{true},

ε_{C} = a {[\overset{{((), normald C true/ normald z)}^{2}}{true}]}^{b},

Section: Observationsmentioning

confidence: 99%

“…To infer the dissipation rate from the YODA Profiler, ε C , we assumed the dissipation rate followed

ε_{C} = a {[\overset{{((), normald C true/ normald z)}^{2}}{true}]}^{b},

Section: Observationsmentioning

confidence: 99%

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Strong turbulent mixing induced by internal bores interacting with internal tide‐driven vertically sheared flow

Masunaga

Fringer

Yamazaki

et al. 2016

Geophysical Research Letters

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“…Although the YODA Profiler data may be used to estimate the rate of turbulent kinetic energy dissipation,

ε

, this method requires a mapping function between the variance of the vertical gradient of the conductivity signal, ∂ C /∂ z , and

ε

using a direct comparison between microstructure data and the YODA Profiler data (Masunaga & Yamazaki, ). We did not have access to a microstructure profiler; thus the Masunaga and Yamazaki method could not be applied.…”

Section: Discussionmentioning

confidence: 99%

“…We also used a similar towed ADCP (RiverRay) to monitor the three‐dimensional flow around salmon cages in Fløya Island, Norway. In order to obtain waste material data, we employed a multi‐parameter free‐fall profiler YODA (Yoing Ocean Data Acquisition) Profiler; Masunaga & Yamazaki, ), which can provide high‐resolution measurements of physical/biological structures in shallow coastal waters. This paper describes how the combination of a towed ADCP and YODA Profiler can be useful for measuring the flow field and effluent transport around fish cages.…”

Section: Introductionmentioning

confidence: 99%

Observation of three-dimensional flow structures and effluent transport around fish cages using a towed ADCP and free-fall multi-parameter profiler

et al. 2019

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A field campaign was conducted around salmon cages, using a combination of a towed ADCP and a free‐fall multi‐parameter profiler, in order to investigate flow structures and the possible distribution of effluent materials. Two transect observations showed that hydrographic conditions changed dramatically within 5 days, from highly stratified open water conditions to weak stratification. Three‐dimensional observation revealed that flow was blocked behind the cages and that the blockage was reduced as the distance from the cages increased. The flow speed was positively correlated with the intensity of the backscattering signal. The R2 value was high immediately behind the cages and decreased with distance from the cages. The flow time series behind the cages exhibited a k–2 power law spectrum that was consistent with a typical internal wave spectrum. This suggests that eddies shed from the cages were highly influenced by stratification. We estimated the rate of kinetic energy dissipation, ε, from YODA Profiler data based on the Thorpe scale approach. We also estimated the eddy diffusivity coefficient, Kρ. Both ε and Kρ followed a lognormal probability density function. The mean Kρ was consistent with a one‐dimensional diffusion model assessed from the R2 values of flow speed and backscatter intensity.

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Stratification and mixing processes associated with hypoxia in a shallow lake (Lake Kasumigaura, Japan)

Masunaga

Komuro

2019

Limnology

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A new tow-yo instrument to observe high-resolution coastal phenomena

Cited by 30 publications

References 45 publications

Strong turbulent mixing induced by internal bores interacting with internal tide‐driven vertically sheared flow

Strong turbulent mixing induced by internal bores interacting with internal tide‐driven vertically sheared flow

Observation of three-dimensional flow structures and effluent transport around fish cages using a towed ADCP and free-fall multi-parameter profiler

Stratification and mixing processes associated with hypoxia in a shallow lake (Lake Kasumigaura, Japan)

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