Ca. Fiebrich et Kc. Crawford, The impact of unique meteorological phenomena detected by the Oklahoma Mesonet and ARS Micronet on automated quality control, B AM METEOR, 82(10), 2001, pp. 2173-2187
To ensure quality data from a meteorological observing network, a well-desi
gned quality control system is vital. Automated quality assurance (QA) soft
ware developed by the Oklahoma Mesonetwork (Mesonet) provides an efficient
means to sift through over 500 000 observations ingested daily from the Mes
onet and from a Micronet sponsored by the Agricultural Research Service of
the United States Department of Agriculture (USDA). However, some of nature
's most interesting meteorological phenomena produce data that fail many au
tomated QA tests. This means perfectly good observations are flagged as err
oneous.
Cold air pooling, "inversion poking," mesohighs, mesolows, heat bursts, var
iations in snowfall and snow cover, and microclimatic effects produced by v
ariations in vegetation are meteorological phenomena that pose a problem fo
r the Mesonet's automated QA tests. Despite the fact that the QA software h
as been engineered for most observations of real meteorological phenomena t
o pass the various tests-but is stringent enough to catch malfunctioning se
nsors-erroneous flags are often placed on data during extreme events.
This manuscript describes how the Mesonet's automated QA tests responded to
data captured from microscale meteorological events that, in turn, were fl
agged as erroneous by the tests. The Mesonet's operational plan is to catal
og these extreme events in a database so QA flags can be changed manually b
y expert eyes.