Quality control of ε estimates (QA2)

From Atomix
Revision as of 20:50, 3 June 2022 by Yuengdjern (talk | contribs)

Quality control measures for each beam:

  1. Data segments for which the regression coefficient a1 (see previous step) is negative yield an imaginary [math]\displaystyle{ \varepsilon }[/math] value, which should be rejected
  2. Ensure sufficient [math]\displaystyle{ D_{ll} }[/math] samples were used in the regression.
  3. Use the coefficient [math]\displaystyle{ a_0 }[/math] (the intercept of the regression) to estimate the noise of the velocity observations and compare to the expected value based on the instrument settings. If noise is too high, [math]\displaystyle{ \epsilon }[/math] are rejected.
  4. Data segments for which the regression coefficient a0 (see previous step) is negative (implying a negative noise floor) are likely to be invalid and are typically rejected
  5. In the case of [math]\displaystyle{ \epsilon }[/math] estimated using the modified regression method that accounts for oscillatory motion, reject data for invalid values of [math]\displaystyle{ A_3 }[/math].
  6. A better indication of the quality of the fit is usually provided by looking at the ratio of the estimated [math]\displaystyle{ \varepsilon }[/math] value to that based on the 95%-ile confidence interval estimate of the a1 regression coefficient e.g. reject values where the ratio exceeds a specified threshold
  7. The goodness of fit (R2) for the regression provides a basic indication of the quality of the fit, data with low R2 are typically rejected.

Other measures (not flagged):

  1. Examine the distribution of [math]\displaystyle{ \varepsilon }[/math] estimates - in most situations, this would be expected to be log-normal
  2. Comparison of observed values with nominal values based on established boundary-forced scalings may also be informative and help to identify observation or processing issues

Quality control measures for final [math]\displaystyle{ \epsilon }[/math] estimate:

  1. Examine the consistency of [math]\displaystyle{ \varepsilon }[/math] between bins (if evaluated) and between beams as an indication of estimate reliability - the geometric mean between beams is frequently used as the representative value

[In progress]


How ADCP structure function quality-control flags are applied

The Q (quality control) flags associated with shear-probe measurements are not compatible with the Ocean Sites Ocean Sites for quality control (QC) coding.

Every dissipation estimate from every probe must have Q flag. The numerical values of the Q flags are as follows:

Flag Mask Bit Flag Meaning Example threshold value Ex: True =1 / False =0 Ex: Q value
1 Bit 0 if FOM > FOM_limit 2 0 0
2 Bit 1 if despike_fraction > despike_fraction_limit 40% 0 0
4 Bit 2 log(e_max)-log(e_min)|> diss_ratio_limit X \sigma_{\ln\varepsilon} N/A 1 4
8 Bit 3 if despike_iterations > despike_iterations_limit To be confirmed 0 0
16 Bit 4 if variance resolved less than a threshold 50% 1 16
32 Bit 5 manual flag to be defined by user N/A 0 0
64 Bit 6 manual flag to be defined by user N/A 0 0
128 Bit 7 manual flag to be defined by user N/A 0 0
Final Q = 20


The Q flags are combined by their addition. For example a Q value of 20 means that the dissipation estimated failed both dissipation ratio limit test and the resolved variance test. A value of 255 means that all tests failed. The reasons for a failure can be decoded by breaking the value of Q down to its powers of 2.


Return to ADCP Flow Chart front page