Deployment

In order to collect useful measurements that actually resolve the turbulence statistics consistent with the application of the Kolmogorov hypotheses, it is important to configure and deploy your instrument using best practice. This requires considerations of:

1. Environmental conditions
   1. Ensure velocity range is sufficient for anticipated background flow, tides, surface waves and internal waves
   2. For pulse-pulse coherent measurements, need to minimise potential issues due to phase wrapping (ambiguity velocity)
   3. Select spatial range (number of bins and bin size) consistent with eddy inertial range Ozmidov length, [math]\displaystyle{ L_o }[/math] [LINK to DEFINITION ON NOMENCLATURE PAGE] given anticipated stratification and turbulence levels
2. Velocity measurements
   1. Record in Beam coordinates​
   2. Maximise velocity accuracy whilst minimising averaging (pings per ensemble)
   3. Select [math]\displaystyle{ \varepsilon }[/math] estimate observation period (period over which structure function is evaluated) consistent with fundamental requirement of stationary statistics
   4. Maximise the number of profiles (ensembles) per [math]\displaystyle{ \varepsilon }[/math] estimate observation period to improve statistics
3. Motion control​ during deployment
   1. Sufficient buoyancy on frame to hold position well, but not obstructing beam path ​
   2. Consider also nearby moorings and frames to reduce/avoid interference.
   3. If the mooring can move, collect depth (pressure sensor on ADCP or adjacent instrument) and orientation data (heading, pitch and roll) at the same frequency as the velocity profiles data. Consider high resolution add-on’s such as AHRS. ​
   4. Mooring design should consider impact of knock-down on location of observations in the water column
   5. Vertical beam in different mode such as alternating high resolution repetition rate?​
4. Power and Storage ​for self-contained deployments
   1. Planned deployment duration
   2. Manufacturer’s expected energy consumption versus battery capacity at expected temperature
   3. Manufacturer’s expected memory required per recorded profile (ensemble) versus available memory
   4. Extending interval between observation periods (burst mode) reduces duty cycle allowing longer duration deployment but with reduced temporal resolution of [math]\displaystyle{ \varepsilon }[/math] estimates

SUGGEST REMOVING BOTH OF THE FOLLOWING PAGES

1. ADCP Hardware
2. ADCP Environment

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