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> within <math>r_{max}</math>  using either a [[bin-centred difference scheme]] or a [[forward-difference]] scheme.  
# Calculate the structure function <math>D_{ll}</math> for all possible bin separations <math>\delta</math> within <math>r_{max}</math>  using either a [[bin-centred difference scheme]] or a [[forward-difference]] scheme.  
# 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.
# Perform a 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 [[Regressing structure function against bin separation | special considerations for forward-difference, center-difference schemes]] in setting up the regression calculation.  The regression is typically done as a least-squares fit, either as: <br /><br /> <math>D_{ll} = a_0 + a_1 (\delta r_0)^{2/3}</math>; or as <br /> <math>D_{ll} = a_0 + a_1 (\delta r_0)^{2/3}+a_3((\delta r_0)^{2/3})^3 </math> <br /><br /> the former being the [[canonical structure function method | canonical method]] that excludes non-turbulent velocity differences between bins, whereas the latter is a [[modified structure function method | modified method]] that includes non-turbulent velocity differences between bins due to any oscillatory signal (e.g. surface waves, motion of the ADCP on a mooring).
# 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 10:46, 10 December 2021

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

Schematic showing along-beam distance r and radial velocities.
  1. Extract or compute the along-beam bin center separation [δr0] 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 within rmax using either a bin-centred difference scheme or a forward-difference 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 in setting up the regression calculation. The regression is typically done as a least-squares fit, either as:

    Dll=a0+a1(δr0)2/3; or as
    Dll=a0+a1(δr0)2/3+a3((δr0)2/3)3

    the former being the canonical method that excludes non-turbulent velocity differences between bins, whereas the latter is a modified method that includes non-turbulent velocity differences between bins due to any oscillatory signal (e.g. surface waves, motion of the ADCP on a mooring).
  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.




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

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

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