Articles | Volume 17, issue 6
Research article
19 Mar 2020
Research article |  | 19 Mar 2020

A robust data cleaning procedure for eddy covariance flux measurements

Domenico Vitale, Gerardo Fratini, Massimo Bilancia, Giacomo Nicolini, Simone Sabbatini, and Dario Papale


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (11 Nov 2019) by Martin De Kauwe
AR by Domenico Vitale on behalf of the Authors (20 Dec 2019)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (08 Jan 2020) by Martin De Kauwe
RR by Anonymous Referee #2 (20 Jan 2020)
RR by Andrew Kowalski (23 Jan 2020)
ED: Publish subject to minor revisions (review by editor) (23 Jan 2020) by Martin De Kauwe
AR by Domenico Vitale on behalf of the Authors (03 Feb 2020)  Author's response    Manuscript
ED: Publish as is (06 Feb 2020) by Martin De Kauwe
Short summary
This work describes a data cleaning procedure for the detection of eddy covariance fluxes affected by systematic errors. We believe that the proposed procedure can serve as a basis toward a unified quality control strategy suitable for the centralized data processing pipelines, where the use of completely data-driven and scalable procedures that guarantee high-quality standards and reproducibility of the released products constitutes an essential prerequisite.
Final-revised paper