Articles | Volume 16, issue 12
Research article
21 Jun 2023
Research article |  | 21 Jun 2023

A data-driven persistence test for robust (probabilistic) quality control of measured environmental time series: constant value episodes

Najmeh Kaffashzadeh

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Cited articles

Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res.-Atmos., 106, 23073–23095,, 2001. 
Box, G. E. P., Jenkins, G. M., Reinsel, G. C., and Ljung, G. M.: Time series analysis: forecasting and control, 5th edn., John Wiley & Sons, Inc, Hoboken, New Jersey, 712 pp., ISBN: 978-1-118-67502-1, 2015. 
Bushnell, M., Waldmann, C., Seitz, S., Buckley, E., Tamburri, M., Hermes, J., Heslop, E., and Lara-Lopez, A.: Quality Assurance of Oceanographic Observations: Standards and Guidance Adopted by an International Partnership, Frontiers in Marine Science, 6, 706,, 2019. 
Campbell, J. L., Rustad, L. E., Porter, J. H., Taylor, J. R., Dereszynski, E. W., Shanley, J. B., Gries, C., Henshaw, D. L., Martin, M. E., Sheldon, W. M., and Boose, E. R.: Quantity is Nothing without Quality: Automated QA/QC for Streaming Environmental Sensor Data, BioScience, 63, 574–585,, 2013. 
Castelão, G. P.: A Flexible System for Automatic Quality Control of Oceanographic Data, arXiv [preprint],, 17 November 2016. 
Short summary
Although quality control is a well-known issue in data application, research initiatives and organizations apply given methods based on traditional techniques (ad hoc thresholds and manual). These approaches are not only error prone but also unsuitable for a large volume of data. The method proposed in this paper is based on a new concept (probability) as an intuitive indicator and data’s characteristics, which leads it to be applicable to a wide variety of data and eases its fit for purpose.