In order to collect useful measurements that '''actually resolve''' the turbulence statistics consistent with the application of the Kolmogorov hypotheses of [[isotropic turbulence]], it is important to configure and deploy your instrument using best practices. In setting up your instrument, it is recommended that consider the following:
In order to collect useful measurements that '''actually resolve''' the turbulence statistics consistent with the application of the Kolmogorov hypotheses of [[isotropic turbulence]], it is important to configure and deploy your instrument using best practices. In setting up your instrument, please consider the following reccomendations:
==Environmental Conditions ==
==Environmental Conditions ==
Revision as of 12:39, 8 December 2021
In order to collect useful measurements that actually resolve the turbulence statistics consistent with the application of the Kolmogorov hypotheses of isotropic turbulence, it is important to configure and deploy your instrument using best practices. In setting up your instrument, please consider the following reccomendations:
Ensure measurement velocity range is sufficient for anticipated background flow, tides, surface waves and internal waves
For pulse-pulse coherent measurements, minimize potential issues due to phase wrapping by setting the ambiguity velocity to be larger than the maximum flow speed that is expected
Ensure that spatial parameters (number of bins and bin size) are selected so that several bins are within the expected inertial subrange that extends from the Kolmogorov scale [math]\displaystyle{ L_K }[/math] to the Ozmidov scale [math]\displaystyle{ L_o }[/math] . Use anticipated stratification and turbulence levels to determine [math]\displaystyle{ L_K }[/math] and [math]\displaystyle{ L_o }[/math] for the deployment location.
Velocity Measurements
Record raw data in along-beam coordinates
Maximise velocity accuracy whilst minimising averaging (pings per ensemble)
If using a duty cycle, ensure that each burst is long enough to obtain stationary statistics necessary for [math]\displaystyle{ \varepsilon }[/math] estimates
Maximise the number of profiles (ensembles) per [math]\displaystyle{ \varepsilon }[/math] estimate observation period to improve statistics
Avoid/reduce interference with nearby instruments to reduce/avoid interference by sampling at different intervals.
For instruments with an extra (vertical) beam, select the desired configuration of the angled beams
Motion control during deployment
For bottom mounted instruments, minimise motion by ensuring that the frame is sufficiently heavy and streamlined to withstand the flow conditions at the deployment location
For moored instruments, minimise motion by ensuring there is sufficient buoyancy on frame to hold position well. Also ensure that the buoyancy components do not obstruct beam path
For moored instruments, consider impact of knock-down on location of observations in the water column when designing the mooring
For moored instruments, collect depth and orientation data (heading, pitch and roll) at the same frequency as the velocity profiles data. Depth measurements could be made by the pressure sensor on ADCP or by adjacent instrument. Consider high resolution add-ons such as Altitude and Heading Reference Sensor (AHRS).
Power and Storage for self-contained deployments
Ensure the battery and memory capacity are sufficient for the planned deployment duration
Factor in the expected water temperature when estimating the battery capacity and energy consumption
Factor in the available memory and the manufacturer’s expected memory required per recorded profile (ensemble) when estimating the memory capacity
For long deployments, extend the interval between observation periods (burst mode). This allows for longer duration deployments but reduces the temporal resolution of [math]\displaystyle{ \varepsilon }[/math] estimates
