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The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Author Pastorello Gilberto, Trotta Carlo, Canfora Eleonora, Chu Housen, Christianson Danielle, Cheah You-Wei, Poindexter Cristina, Chen Jiquan, Elbashandy Abdelrahman, Humphrey Marty, Isaac Peter, Polidori Diego, Reichstein Markus, Ribeca Alessio, van Ingen Catharine, Vuichard Nicolas, Zhang Leiming, Amiro Brian, Ammann Christof, Arain M. Altaf, Ardö Jonas, Arkebauer Timothy, Arndt Stefan K., Arriga Nicola, et al. ,
Project ICOS-CH Phase 2
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Original article (peer-reviewed)

Journal Scientific Data
Volume (Issue) 7(1)
Page(s) 225 - 225
Title of proceedings Scientific Data
DOI 10.1038/s41597-020-0534-3

Open Access

URL http://doi.org/10.1038/s41597-020-0534-3
Type of Open Access Publisher (Gold Open Access)

Abstract

Abstract The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.
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