3.3
Quality Assurance Methods for the Kentucky Mesonet
Megan M. Ferris, Western Kentucky University, Bowling Green, KY; and S. Struebig, M. Grogan, S. Foster, and R. Mahmood
The Kentucky Mesonet is a real-time meteorological observing network being deployed across the Commonwealth of Kentucky. High quality data from these stations is important for research and operational use. Instruments selected for the project are calibrated in the Kentucky Mesonet instrumentation laboratory and at the experimental testing bed located at the Western Kentucky University agriculture farm. Once calibrated, the instrumentation is installed at the remote stations. Observed data is stored locally on the station datalogger. Remote collection of data occurs via cellular modem communications. Raw data is stored in a database until later used in the quality assurance (QA) process.
Data from the stations undergo multiple levels of quality assurance in order to ensure the data meets research standards. Kentucky Mesonet technicians perform routine maintenance at each of the remote stations. Duties include vegetation maintenance, instrument rotation, and photographic documentation. Problems that arise between scheduled visits are investigated and a trouble ticket describing the problem, suggested actions to take, and priority value is assigned if the problem requires human intervention.
Raw data is queried – never changed – from the database to apply quality assurance methods. Automated QA is a series of computer scripts written to perform preliminary checks on the data, including instrument range checks and step tests, as well as algorithms developed for instrument intercomparison. If data fails to pass any individual step of this process, it does not proceed to the next step until it is manually checked by the quality assurance staff.
At this point, the data is assigned a quality value based on the confidence of the data being valid or invalid. Station metadata, or data about data, recorded during site installation or maintenance is a vital key in the determination of data quality. Further investigation of meteorological conditions combined with metadata allows the QA meteorologist to effectively assign the proper value to the data. For example, a station located in a valley or forested area tends to have much cooler nighttime temperatures than a station on a hill or open, flat area.
Another important feature present is redundant instrumentation at the station. One example is temperature measurement: three fast response temperature sensors are located inside of an aspirated shield and a slower response temperature and relative humidity sensor is located inside of an unaspirated shield. While only the three aspirated sensors are used for the official air temperature calculation, the additional unaspirated sensor assists in the QA process by providing an upper limit of reasonable air temperature at the given time. This redundancy also reduces the urgency for spatial temperature comparison as well as increasing the likelihood of a correct temperature measurement/calculation. After all QA steps have been completed, the finished dataset is stored in a database.
In the future, complex automated QA techniques will be incorporated into the routine to ease the load of manual QA. The development of the QA system will continue as the Kentucky Mesonet grows.
Session 3, Data quality control
Monday, 18 January 2010, 4:00 PM-5:30 PM, B302
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