Processing your ADCP data using structure function techniques: Difference between revisions

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# Select the maximum distance (<math>r_{max}</math>) over which to compute the structure function based on conditions of the flow (e.g., expected max overturn). The corresponding number of bins is [<math>n_{\text{rmax}} = r_{max} / r_0</math>]
# Select the maximum distance (<math>r_{max}</math>) over which to compute the structure function based on conditions of the flow (e.g., expected max overturn). The corresponding number of bins is [<math>n_{\text{rmax}} = r_{max} / r_0</math>]
# Calculate the structure function <math>D_{ll}</math> for all possible bin separations <math>\delta</math> using either a [[bin-centred difference scheme]] or a [[forward-difference]] scheme. Consider [[Final data review (QA2) | QA2 requirements]] when choosing differencing scheme.  
# Calculate the structure function <math>D_{ll}</math> for all possible bin separations <math>\delta</math> using either a [[bin-centred difference scheme]] or a [[forward-difference]] scheme. Consider [[Final data review (QA2) | QA2 requirements]] when choosing differencing scheme.  
# Perform a [[Regressing ''D''<sub>ll</sub> against δ | regression ]] of <math>D_{ll}(n,\delta)</math> against <math>(\delta r_0)^{2/3}</math> for the appropriate range of bins and <math>\delta</math>r<sub>0</sub> separation distances. Be aware of special considerations for forward-difference, center-difference schemes.   
# Perform a [[Regressing structure function against bin separation | regression of <math>D_{ll}(n,\delta)</math> against <math>(\delta r_0)^{2/3}</math>]] for the appropriate range of bins and <math>\delta</math>r<sub>0</sub> separation distances. Be aware of special considerations for forward-difference, center-difference schemes.   
# Use the coefficient <math>a_1</math> to calculate <math>\varepsilon</math> as <br /><br /> <math>\varepsilon = \left(\frac{a_1}{C_2}\right)^{2/3}</math> <br /><br /> where <math>C_2</math> is an [[ Structure function empirical constant | empirical constant]], typically taken as 2.0 or 2.1.  
# Use the coefficient <math>a_1</math> to calculate <math>\varepsilon</math> as <br /><br /> <math>\varepsilon = \left(\frac{a_1}{C_2}\right)^{2/3}</math> <br /><br /> where <math>C_2</math> is an [[ Structure function empirical constant | empirical constant]], typically taken as 2.0 or 2.1.  



Revision as of 16:23, 15 November 2021

To calculate the dissipation rate at a specific range bin and a specific time ensemble:

  1. Extract or compute the along-beam bin center separation [r0] based on the instrument geometry
  2. Calculate the along-beam velocity fluctuation time-series in each bin n, where [Failed to parse (syntax error): {\displaystyle v’(n, t)} ] from the along-beam velocity data that has met the QC criteria (i.e. the data in Level 2 of the netcdf file)
  3. Select the maximum distance (rmax) over which to compute the structure function based on conditions of the flow (e.g., expected max overturn). The corresponding number of bins is [nrmax=rmax/r0]
  4. Calculate the structure function Dll for all possible bin separations δ using either a bin-centred difference scheme or a forward-difference scheme. Consider QA2 requirements when choosing differencing scheme.
  5. Perform a regression of Dll(n,δ) against (δr0)2/3 for the appropriate range of bins and δr0 separation distances. Be aware of special considerations for forward-difference, center-difference schemes.
  6. Use the coefficient a1 to calculate ε as

    ε=(a1C2)2/3

    where C2 is an empirical constant, typically taken as 2.0 or 2.1.


PERHAPS WE CAN INCLUDE A FIGURE LIKE THIS TO HELP DEFINE VARIABLES.

Next step: Apply quality-control on velocity time series data (QA1)

Previous step: Apply quality-control on dissipation rates (QA2)

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