Flow chart for shear probes

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Revision as of 09:55, 28 August 2023 by Ilker (talk | contribs)

The processing of shear-probe data can be divided into the following five major steps and these steps apply to data collected with any platform or vehicle. There are many sub-steps to these major steps. The major steps are:

Conversion to physical units


As a first step, the raw binary data needs to be transformed into physical units.


Please note that most choices made must be included in a data set, as described in the list of meta data.

"Section" selection


Before you can process your shear-probe data to derive the rate of dissipation you must select the section of data that you wish to process. For a vertically profiling instrument, this is traditionnally referred to as a "profile". We adopt the term "section" as this is platform independent and will include time series for dissipation estimates along horizontal or slanted trajectories as well as from moored shear probes. You must make sure that the selection is meaningful and sensible. For example, the shear probe must be profiling through the water with a speed, direction, and orientation that is fairly stationary. The selection of data can be partially automated by requiring that the kinematics of your instrument achieve certain minimum criteria. The steps to section selection are as follows:

Choosing the processing parameters


Compute the dissipation rate estimates


The following steps are recommended to obtain estimates of the turbulent dissipation rate of kinetic energy ([math]\displaystyle{ \varepsilon }[/math]).

  1. Extract the section to estimate dissipation time series ("Section" selection).
  2. High-pass filter the shear-probe and (optionally) the vibration data.
  3. Identify each diss-length segment in the section.
  4. De-spike the shear-probe data, and track the fraction of data affected by de-spiking within each diss-length segment. This will become a quality-control metric.
  5. Calculate the frequency spectra and cross-spectra of shear and vibrations for each diss-length segment.
  6. Extract the original and the vibration-coherent clean shear-probe frequency spectra with the Goodman algorithm.
  7. Correct shear and vibration frequency spectra for the high-pass filter.
  8. Correct the cleaned frequency spectra for the bias induced by the Goodman algorithm.
  9. Convert the frequency spectra into wavenumber spectra using the mean speed, [math]\displaystyle{ U }[/math], for each diss-length segment. That is, make the wavenumber [math]\displaystyle{ k=f/U }[/math] and the spectrum [math]\displaystyle{ E(k)=UE(f) }[/math] .
  10. Correct the spectra of shear for the wavenumber response of the shear probe.
  11. Apply an iterative spectral integration algorithm to estimate the variance of shear.
  12. Calculate the turbulent dissipation rate by multiplying the shear variance by [math]\displaystyle{ \frac{15}{2}\nu }[/math] where [math]\displaystyle{ \nu }[/math] is the temperature-dependent kinematic viscosity.
  13. Determine the figure of merit (FM) for each shear-probe spectrum.
  14. Calculate the expected variance of each dissipation estimate.

Apply quality-control metrics


Shear-probe data can be corrupted or compromised in several different ways. These include but are not limited to (i) collision with plankton and other materials, (ii) unremovable vibrational contamination. (iii) electronic noise, and (iv) interference from other instrumentation on a platform that carries the shear probes. This section describes the quality control metrics and the coding used to identify them. Quality-control metrics that are currently identified include;

The numerical threshold for these metrics should depend, as much as possible, on the known statistical properties of a turbulence shear measurement. The numerical values of the QC codes (or flags) is found in QC-flags.



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