Articles | Volume 17, issue 6
https://doi.org/10.5194/bg-17-1367-2020
https://doi.org/10.5194/bg-17-1367-2020
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

Model code and software

RFlux: An R Package for Processing and Cleaning Eddy Covariance Flux Measurements D. Vitale, D. Papale, and ICOS-ETC Team https://github.com/icos-etc/RFlux

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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.
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