Articles | Volume 13, issue 12
Atmos. Meas. Tech., 13, 6945–6964, 2020
https://doi.org/10.5194/amt-13-6945-2020
Atmos. Meas. Tech., 13, 6945–6964, 2020
https://doi.org/10.5194/amt-13-6945-2020

Research article 21 Dec 2020

Research article | 21 Dec 2020

Effects of the prewhitening method, the time granularity, and the time segmentation on the Mann–Kendall trend detection and the associated Sen's slope

Martine Collaud Coen et al.

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Cited articles

Bader, S., Collaud Coen, M., Duguay-Tezlaff, A., Frei, C., Fukutome, S., Gehrig, R., Maillard Barras, E., Martucci, G., Romanens, G., Scherrer, S., Schlegel, T., Spirig, C., Stübi, R., Vuilleumier, L., and Zubler, E.: Klimareport 2018, edited by: Bundespublikationen BBL, Artikelnummer 313.001.d, 94 pp., ISSN: 2296-1488, MeteoSchweiz, Bundesamt für Meteorologie und Klimatologie MeteoSchweiz, Zürich, available at: https://www.meteoswiss.admin.ch/content/dam/meteoswiss/de/service-und-publikationen/Publikationen/doc/klimareport_2018_de.pdf (last access: 30 November 2020), 2019. 
Bayazit, M. and Önöz, B.: To prewhiten or not to prewhiten in trend analysis?, Hydrolog. Sci. J., 52, 611–624, https://doi.org/10.1623/hysj.53.3.669, 2007. 
Bayazit, M., Önöz, B., Yue, S., and Wang, C.: Comment on “Applicability of prewhitening to eliminate the influence of serial correlation on the Mann-Kendall test” by Sheng Yue and Chun Yuan Wang, Water Resour. Res., 40, W08801, https://doi.org/10.1029/2002WR001925, 2004. 
Bigi, A. and Vogt, F. P. A.: mannkendall/R: First release, Version v1.0.0, Zenodo, https://doi.org/10.5281/zenodo.4134633, 2020. 
Short summary
The Mann–Kendall trend test requires prewhitening in the presence of serially correlated data. The effects of five prewhitening methods and time granularity, autocorrelation, temporal segmentation and length of the time series on the statistical significance and the slope are studies for seven atmospheric datasets. Finally, a new algorithm using three prewhitening methods is proposed in order to optimize the power of the test, the amount of erroneous false positive trends and the slope estimate.