2000
DOI: 10.1175/1520-0426(2000)017<0474:qapito>2.0.co;2
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Quality Assurance Procedures in the Oklahoma Mesonetwork

Abstract: High quality data sources are critical to scientists, engineers, and decision makers alike. The models that scientists develop and test with quality-assured data eventually become used by a wider community, from policy makers' long-term strategies based upon weather and climate predictions to emergency managers' decisions to deploy response crews. The process of developing high quality data in one network, the Oklahoma Mesonetwork (Mesonet) is detailed in this manuscript. The Oklahoma Mesonet quality-assurance… Show more

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Cited by 240 publications
(190 citation statements)
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“…The raw data record at the three sites is largely but not entirely complete. We imputed a minimal amount of isolated missing data (less than 0.03% for calendar year 2003) and adopted the quality assurance procedures proposed by Shafer et al (2000) and Fiebrich and Crawford (2001). Specifically, we applied range, step and persistence tests to the raw data at the 10-minute aggregation level.…”
Section: The Meteorological Towers At Vansycle Kennewick and Goodnoementioning
confidence: 99%
“…The raw data record at the three sites is largely but not entirely complete. We imputed a minimal amount of isolated missing data (less than 0.03% for calendar year 2003) and adopted the quality assurance procedures proposed by Shafer et al (2000) and Fiebrich and Crawford (2001). Specifically, we applied range, step and persistence tests to the raw data at the 10-minute aggregation level.…”
Section: The Meteorological Towers At Vansycle Kennewick and Goodnoementioning
confidence: 99%
“…In addition, each Mesonet site deployed as part of OKCNET includes sensors to measure air temperature at 9 m. All Oklahoma Mesonet data are collected and transmitted to a central point every 5 minutes where they are quality controlled, distributed and archived [35,37,38].…”
Section: Methodsmentioning
confidence: 99%
“…In all cases, estimated values calculated from neighbouring sites are compared to observed values and large deviations are flagged as potential errors. Shafer et al (2000) use a weighted average of neighbouring stations to calculate a value for the station being checked, with differences exceeding three standard deviations flagged as suspicious. In mountain regions, Lanzante (1996) suggests 10 using vertical neighbours (closest station with a similar elevation) as an alternative to horizontal proximity.…”
Section: Neighbourhood Consistencymentioning
confidence: 99%