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

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  • Gilberto Pastorello
  • Carlo Trotta
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  • Ivan Schroder
  • Russell L. Scott
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  • Penelope Serrano-Ortiz
  • Changliang Shao
  • Peili Shi
  • Ivan Shironya
  • Lukas Siebicke
  • Ladislav Sigut
  • Richard Silberstein
  • Costantino Sirca
  • Donatella Spano
  • Rainer Steinbrecher
  • Robert M. Stevens
  • Cove Sturtevant
  • Andy Suyker
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  • Juha-Pekka Tuovinen
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  • Riccardo Valentini
  • Michiel van der Molen
  • Eva van Gorsel
  • Ko van Huissteden
  • Andrej Varlagin
  • Joseph Verfaillie
  • Timo Vesala
  • Caroline Vincke
  • Domenico Vitale
  • Natalia Vygodskaya
  • Jeffrey P. Walker
  • Elizabeth Walter-Shea
  • Huimin Wang
  • Robin Weber
  • Sebastian Westermann
  • Christian Wille
  • Steven Wofsy
  • Georg Wohlfahrt
  • Sebastian Wolf
  • William Woodgate
  • Yuelin Li
  • Roberto Zampedri
  • Junhui Zhang
  • Guoyi Zhou
  • Donatella Zona
  • Deb Agarwal
  • Sebastien Biraud
  • Margaret Torn
  • Dario Papale

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, 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.

OriginalsprogEngelsk
Artikelnummer225
TidsskriftScientific Data
Vol/bind7
Udgave nummer1
Antal sider27
ISSN2052-4463
DOI
StatusUdgivet - 2020

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