Deployment: Difference between revisions
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* Record raw data in along-beam coordinates | * Record raw data in along-beam coordinates | ||
* Maximise velocity accuracy whilst minimising averaging (pings per ensemble) | * 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>\varepsilon</math> estimates | * If using a duty cycle, ensure that each [[Burst sampling|burst]] is long enough to obtain stationary statistics necessary for <math>\varepsilon</math> estimates | ||
* Maximise the number of profiles (ensembles) per <math>\varepsilon</math> estimate observation period to improve statistics | * Maximise the number of profiles (ensembles) per <math>\varepsilon</math> estimate observation period to improve statistics | ||
* Avoid/reduce interference with nearby instruments to reduce/avoid interference by sampling at different intervals. | * Avoid/reduce interference with nearby instruments to reduce/avoid interference by sampling at different intervals. | ||
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* Factor in the expected water temperature when estimating the battery capacity and energy consumption | * 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 | * 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>\varepsilon</math> estimates | * For long deployments, extend the interval between observation periods ([[Burst sampling|burst mode]]). This allows for longer duration deployments but reduces the temporal resolution of <math>\varepsilon</math> estimates | ||
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Latest revision as of 19:20, 8 March 2022
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
Velocity Measurements
Motion control during deployment
Power and Storage for self-contained deployments
Next Step: Raw data review (QA1)
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