Archive > Volume 44 Issue 6 > 2016,44(6):882-888 Prev Next

Algorithm Design of Fast and RealTime Quality Control forPrecipitation Data from Automatic Stations

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    Abstract:
    Quality control （QC） methods for Automatic Weather Stations （AWS） precipitation data are combined to design a fast and realtime QC Algorithm. Abnormal precipitation data are classified firstly. The Grubbs test is then used to screen out suspicious stations in a local and finite space preliminarily. Three factors are considered in the second step of the QC procedure, which are the spatial distribution of precipitation per hour, the timehistory equation of precipitation per minute, and the related characteristics between temperature and humidity. Practical test shows that the integrated quality control algorithm has a better balance between performance and accuracy, which is especially effective in summer.

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External LinksChina Meteorological AdministrationCMA Meteorological Observation CentreChinese Academy of Meteorological SciencesBeijing Meteorological ServiceNational Satellite Meteorological Center
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