The ECA&D data-set collects over 81000 series of observations for the Essential Climate Variables more than 22400 stations from all countries in Europe. Large number of these series are affected by outliers, repeated values and other issues in the measurements. These quality issues need to be identified prior to further processing of the data into e.g. the production of the gridded E-OBS datasets as these issues may lead to erroneous estimates of climate impact indices and trends. In the context of the Copernicus contract C3S2_311 Lot3, the MetQC method developed at GCRI has been implemented for operational use at ECA&D. This new method combines checks on duplicate series, repetitive values and outliers with an inter-stations comparison. Earlier work compared five different quality check methods (MetQC, MASH, ACMANT, NOAA, C3QC) on four benchmark data-sets covered by ECA&D. This work indicated that the MetQC approach performed well in comparison against the other methods and the new method replaces the more primitive approach at ECA&D in which straightforward stand-alone tests were conducted. A strong aspect of the MetQC method is that it provides an estimate for an alternative value of a suspect value based on values of surrounding stations, with a quantification of the reliability of this alternative. The MetQC method has been further refined and tailored to the application at ECA&D to be capable of handling the vast dataset in a reasonable time. The presentation will focus on the improvement in quality for ECA&D and comparisons in terms of numbers of flagged data and given between the new approach and the approach it replaces.
How to cite: Stepanek, P., Van der Schrier, G., and Zahradníček, P.: A new quality Control procedure for ECA&D, EMS Annual Meeting 2022, Bonn, Germany, 5–9 Sep 2022, EMS2022-716, https://doi.org/10.5194/ems2022-716, 2022.