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

Collaud Coen, Martine; Andrews, Elisabeth; Bigi, Alessandro; Martucci, Giovanni; Romanens, Gonzague; Vogt, Frédéric P. A.; Vuilleumier, Laurent

doi:https://doi.org/10.5194/amt-13-6945-2020

Articles | Volume 13, issue 12

https://doi.org/10.5194/amt-13-6945-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/amt-13-6945-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 12

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, Elisabeth Andrews, Alessandro Bigi, Giovanni Martucci, Gonzague Romanens, Frédéric P. A. Vogt, and Laurent Vuilleumier

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Final revised paper (published on 21 Dec 2020)
Preprint (discussion started on 17 Jun 2020)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'amt-2020-178_REFEREE REPORT', Wenpeng Wang, 15 Jul 2020
- AC1: 'Responses to Wenpeng Wang', Martine Collaud Coen, 14 Oct 2020
RC2: 'amt-2020-178_REFEREE REPORT', Wenpeng Wang, 15 Jul 2020
- AC2: 'responses to Wenpeng Wang (comments posted twice)', Martine Collaud Coen, 14 Oct 2020
RC3: 'Comments to Coen et al', Anonymous Referee #1, 17 Jul 2020
- AC3: 'Responses to anonymous referee 1', Martine Collaud Coen, 14 Oct 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Katja Gänger on behalf of the Authors (15 Oct 2020) Author's response

ED: Publish as is (16 Oct 2020) by Mark Weber

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.