Unique Quality Control Issues

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Unique Quality Control Issues

• Derek S. Arndt
• Oklahoma Climatological Survey
• June 25, 2002

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OK Mesonet Automated QA

• Range Test
• Does the datum lie within a prescribed min/max?
• Step Test
• Does the datum exhibit a seemingly unrealistic
  jump in a time step?
• Persistence Test
• Does a time series exhibit unrealistically small
  variability?

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OK Mesonet Automated QA

• Spatial Test
• Does an observation conform within a maximum
  tolerable deviation to that of neighboring
  stations?
• Like-instrument Test
• Does an observation significantly deviate from a
  similar instrument elsewhere on the tower?

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Automated QA Flags

• Decision-making algorithm compiles results of
  automated QA tests
• Final flag (good, suspect, warning or
  bad) determined by logic
• The final flag is never final!
• The Qualparm table represents the QA
  Meteorologists latest and best assessment of
  observational quality for the given time
• Automated report arrives in the QA
  Meteorologists inbox each morning.

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Capturing Real Events With Automated QA

• Automated QA software is invaluable as a
  front-line detector
• However, nothing beats the trained eye and brain
  of a QA meteorologist
• Sometimes, unique meteorological events fail QA
  tests and good data is suggested to be bad

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Goodparms

• Goodparms reflect observations that are known to
  be good, but have failed an automated QA test
• In the next generation of OK Mesonet QA
  structure, Goodparm entries will override
  automated QA tests that have been fooled by
  Mother Nature

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Noteworthy Goodparm Events

• The following examples of real meteorological
  phenomena that were initially flagged by
  automated QA processes
• Thanks to automated reporting, and a vigilant QA
  Meteorologist, these bad events turned out to
  be some of the networks gems!

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Inversion Poking

• Extreme spatial anomalies occur
• Air temperature
• Dew point temperature / relative humidity
• Wind direction
• Wind speed
• Associated with shallow inversion and stable
  surface layer

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Inversion Poking
Norman, OK Sounding 25 Oct 2001 1200 UTC
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Inversion Poking
OK Mesonet Sfc Plot 25 Oct 2001 1330 UTC
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Inversion Poking
North Central Oklahoma Elevation (meters)
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Inversion Poking
26 Oct 1999 0600 UTC
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Cold Air Pooling

• Extreme temperature anomalies develop due to
  radiational cooling
• Events tend to occur within a few hours of
  sunset, suggesting in situ cooling (versus cold
  air drainage)
• Radiationally cooled air is prevented from mixing

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Cold Air Pooling
26 Oct 1999 0600 UTC
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Cold Air Pooling
East Central Oklahoma Elevation (meters)
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Cold Air Pooling
4 Nov 1999 1215 UTC
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Mesohighs

• Typically occur concurrently with convective line
  or cluster
• May trigger spatially-oriented QA tests
• May be a traveling QA phenomenon

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Mesohighs
1 Jun 1999 0235 UTC
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Mesohighs
1 Jun 1999 0235 UTC
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Mesohighs
1 Jun 1999 0236 UTC
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Mesolows

• Typically located off the trailing edge of
  convective precipitation
• May be a traveling QA phenomenon

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Mesolows
25 May 2000 0700 UTC
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Mesolows
25 May 2000 0730 UTC
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Mesolows
25 May 2000 0800 UTC
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Mesolows
25 May 2000 0659 UTC
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Mesolows
25 May 2000 0730 UTC
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Mesolows
25 May 2000 0801 UTC
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Heatbursts

• Originate from air that has subsided
  dry-adiabatically from mid-levels of
  outwardly-innocuous thunderstorms
• Downdrafts sometimes cause damaging winds and
  substantial temperature rises
• Heatbursts occur much more often in Oklahoma than
  previously thought

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Heatbursts
20 Sep 1998 1049 UTC
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Heatbursts
20 Sep 1998 1148 UTC
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Heatbursts
20 Sep 1998 1248 UTC
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Heatbursts
Air Temperature 20 Sep 1998 1145 UTC
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Heatbursts
Wind Gusts 20 Sep 1998 1145 UTC
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Heatbursts
Mesonet Meteogram 20-21 Sep 1998
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Winter Precipitation

• Automated QA is quite good at detecting wind
  sensors that accumulate ice and barometers that
  become sealed from the atmosphere
• (P T at constant V!)
• Unique conditions that accompany snowfall can
  sometimes lead to erroneous flags

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Winter Precipitation
Visible Imagery 7 Dec 1999
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Winter Precipitation
Air Temperature 7 Dec 1999 1000 UTC
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Land-Atmosphere-Vegetation

• Soil temperatures are sensitive to the
  characteristics of the soil and vegetation above
  them
• Vegetation of surrounding land areas can impact
  temperature and dew point observations at a site

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Land-Atmosphere-Vegetation
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Land-Atmosphere-Vegetation
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Sloshing and Wave Events
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Thats It!
Heres to bad data! Best of luck to you and
your network! Derek Arndt Oklahoma
Climatological Survey darndt_at_ou.edu