Quality control and processing of the Ocean Research Stations in the Yellow and East China Sea

Abstract

After the construction of the Ieodo Ocean Research Station in 2003, an air-sea integratedmonitoring system installed at the station has observed an atmospheric and oceanic status formore than a decade. Previously, a typical quality control method including data range, gradient,time continuity, spike, and stuck sensor checks, was operated to identify erroneous ormisrepresentative measurements. Although the method classifies a relatively large amount ofmeasurements into erroneous data, white-noise type errors and unrealistic measurements arestill remained. To overcome the drawbacks of the previous method, a newly devised qualitycontrol procedure has been suggested. The new method has two levels of the quality control:automatic and subjective quality control. At the first level, outliers are automatically flaggedbased on a data range check, standard deviation check with various moving windows, and fixedvalue check. At the secondstage, measurements that were likely recorded during cleansing,relocation, or replacement of a sensor are also flagged based on a field note or record, and thensome data has been subjectively flagged by comparing with other relevant observations. Withapplying the quality control system to the surface temperature time series for the period of 2004-2016, we could obtain a qualified time series with that a much smaller amount of values (i.e., afifth of previously flaggrol method including data range, gradient,time continuity, spike, and stuck sensor checks, was operated to identify erroneous ormisrepresentative measurements. Although the method classifies a relatively large amount ofmeasurements into erroneous data, white-noise type errors and unrealistic measurements arestill remained. To overcome the drawbacks of the previous method, a newly devised qualitycontrol procedure has been suggested. The new method has two levels of the quality control:automatic and subjective quality control. At the first level, outliers are automatically flaggedbased on a data range check, standard deviation check with various moving windows, and fixedvalue check. At the secondstage, measurements that were likely recorded during cleansing,relocation, or replacement of a sensor are also flagged based on a field note or record, and thensome data has been subjectively flagged by comparing with other relevant observations. Withapplying the quality control system to the surface temperature time series for the period of 2004-2016, we could obtain a qualified time series with that a much smaller amount of values (i.e., afifth of previously flagg