Deployment: Difference between revisions
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# [[ADCP Environment]] | # [[ADCP Environment]] | ||
Proceed to [[ Raw data review (QA1) ]] | |||
Return to [[ADCP structure function flow chart| ADCP Flow Chart front page]] | Return to [[ADCP structure function flow chart| ADCP Flow Chart front page]] |
Revision as of 20:35, 12 November 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, it is recommended that consider the following recommendations:
- Environmental conditions
- Ensure measurement velocity range is sufficient for anticipated background flow, tides, surface waves and internal waves
- For pulse-pulse coherent measurements, minimise 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 [SHOULD WE QUANTIFY THIS] 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] [IS IT POSSIBLE TO LINK TO APPROPRIATE TABLE?]. 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) [(JMM): IS THERE A TYPICAL PINGS PER ENSEMBLE WE CAN RECOMMEND? (i.e. 1 or 2 are all I used at a high flow site)
- If using a duty cycle, ensure that each burst is long enough to obtain stationary statistics necessary for [math]\displaystyle{ \varepsilon }[/math] estimates [(JMM) I REWORDED THIS FROM '[math]\displaystyle{ \varepsilon }[/math] estimate observation period', but I don't know if it is any less confisuing]
- Maximise the number of profiles (ensembles) per [math]\displaystyle{ \varepsilon }[/math] estimate observation period to improve statistics [(JMM) IS THIS ONLY DETERMINED BY THE SAMPLE RATE?]
- 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 [(JMM) CAN WE BE MORE SPECIFIC HERE? ]]
- 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-on’s such as AHRS. [(JMM) WHAT IS THIS ACRONYM]
- 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
SUGGEST REMOVING BOTH OF THE FOLLOWING PAGES
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