Raw data review (QA1): Difference between revisions

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== Raw data review ==
The objective of the raw data review is to ensure that the velocity data used for the calculation of the structure functions are of good quality before proceeding with the turbulence analysis. Bad data are typically identified from the velocity data themselves and other ancillary data (e.g. correlations). It is recommended that velocity data should be flagged if the following are observed:


The raw data review seeks to identify the Level 1 data that satisfies a range of quality control criteria.  Typical criteria used to identify possible bad data include:
== Data quality is poor ==
<div class="mw-collapsible mw-collapsed" id="poor quality" data-collapsetext="Collapse" data-expandtext="Expand">
Poor data qualifiers include:  
* Low correlation values
* Echo intensity anomalies
* Low percent good values
* Data return rate varies
</div>


# Velocity limits
== Unrealistic velocity values ==
## Check for values outside the nominal measurement range for the instrument configuration
<div class="mw-collapsible mw-collapsed" id="unrealistic" data-collapsetext="Collapse" data-expandtext="Expand">
## Check for evidence of phase wrapping (ambiguity velocity) issues
Velocities are unrealistic if there are
# Correlation coefficient
* Evidence of phase wrapping
## minimum threshold
* Velocities outside nominal measurement range
# Echo intensity
* Velocities outside expected distribution
## false target / “fish” detection
</div>
# Percent good
== Significant instrument motion and orientation ==
## applies to measurement modes with in-instrument averaging across multiple pings per ensemble
<div class="mw-collapsible mw-collapsed" id="motion" data-collapsetext="Collapse" data-expandtext="Expand">
# Orientation (heading, pitch, roll) and depth (if sensor installed)
Reject data if there is:
## deployment as planned?
* High variability in pitch, heading and roll
## indentify specific changes or periodic motion  
* Orientation deviates from expected values
# Along beam velocity
</div>
## data return rate
== Wave or periodic motion contamination ==
## phase wrapping for pulse-pulse coherent observations
<div class="mw-collapsible mw-collapsed" id="waves?" data-collapsetext="Collapse" data-expandtext="Expand">
## periodicity indicating waves or oscillatory motion
## distribution outliers
## burst variance spatial and temporal trends
# Temperature and salinity (if sensors installed)
## indication of changes in local stratification and/or internal wave activity
# Earth coordinate velocity 
## may need to be derived from along-beam velocity
## bin mapping if ADCP orientation isn’t vertical
## error velocity from 4-beam instruments
## comparison with ambiguity velocity to check for possible phase wrapping
## burst variance spatial and temporal trends
## shear over observation range


is a comparison of data between beams, between bins and over time to determine possible anomalies. Note that consideration of spatial and temporal trends may be informed by data from other sensors e.g. meteorological, wave or CTD sensors. The following characteristics should be examined:
* Periodic motion at wave frequencies observed in velocity data
</div>
== Velocity shear is too large ==
<div class="mw-collapsible mw-collapsed" id="highshear" data-collapsetext="Collapse" data-expandtext="Expand">


* earth velocities indicate significant horizontal shear
</div>
== Stationary assumption may be violated ==
<div class="mw-collapsible mw-collapsed" id="nonstationary" data-collapsetext="Collapse" data-expandtext="Expand">
* variance of velocity [[Burst sampling|bursts]] shows spatial or temporal trends
</div>
== Stratification is too large ==
<div class="mw-collapsible mw-collapsed" id="toostratified" data-collapsetext="Collapse" data-expandtext="Expand">
* Temperature and salinity (if available) indicate local stratification
</div>
-----
Next step: [[Processing your ADCP data using structure function techniques | Compute structure functions and dissipation estimates]]<br></br>
Previous step: [[ Deployment ]] <br></br>
Return to [[ADCP structure function flow chart| ADCP Flow Chart front page]]
Return to [[ADCP structure function flow chart| ADCP Flow Chart front page]]
[[Category:Velocity profilers]]

Latest revision as of 19:21, 8 March 2022

The objective of the raw data review is to ensure that the velocity data used for the calculation of the structure functions are of good quality before proceeding with the turbulence analysis. Bad data are typically identified from the velocity data themselves and other ancillary data (e.g. correlations). It is recommended that velocity data should be flagged if the following are observed:

Data quality is poor

Poor data qualifiers include:

  • Low correlation values
  • Echo intensity anomalies
  • Low percent good values
  • Data return rate varies

Unrealistic velocity values

Velocities are unrealistic if there are

  • Evidence of phase wrapping
  • Velocities outside nominal measurement range
  • Velocities outside expected distribution

Significant instrument motion and orientation

Reject data if there is:

  • High variability in pitch, heading and roll
  • Orientation deviates from expected values

Wave or periodic motion contamination

  • Periodic motion at wave frequencies observed in velocity data

Velocity shear is too large

  • earth velocities indicate significant horizontal shear

Stationary assumption may be violated

  • variance of velocity bursts shows spatial or temporal trends

Stratification is too large

  • Temperature and salinity (if available) indicate local stratification

Next step: Compute structure functions and dissipation estimates

Previous step: Deployment

Return to ADCP Flow Chart front page

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