13th Conference on Applied Climatology and the 10th Conference on Aviation, Range, and Aerospace Meteorology

Monday, 13 May 2002: 4:15 PM
The impact of unique meteorological phenomena detected by the Oklahoma Mesonet on automated quality control
Chris A. Fiebrich, Oklahoma Climatological Survey, Norman, OK
Poster PDF (633.0 kB)
To ensure quality data from a meteorological observing network, a well-designed quality control system is vital. Automated quality assurance (QA) software developed by the Oklahoma Mesonetwork (Mesonet) provides an efficient means to sift through over 500,000 observations ingested daily. However, some of natureís most interesting meteorological phenomena produce data that fail many automated QA tests. This means perfectly good observations are flagged as erroneous.

Cold air pooling, "inversion poking", mesohighs, mesolows, heat bursts, variations in snowfall and snowcover, and microclimatic effects produced by variations in vegetation are meteorological phenomena that pose a problem for the Mesonetís automated QA tests. Despite the fact that the QA software has been engineered for most observations of real meteorological phenomena to pass the various tests -- but stringent enough to catch malfunctioning sensors -- erroneous flags are often placed on data during extreme events.

This manuscript describes how the Mesonetís automated QA tests responded to data captured from microscale meteorological events that, in turn, were flagged as erroneous by the tests. The Mesonetís operational plan is to catalog these extreme events in a database so QA flags can be changed manually by expert eyes.

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