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Torbern Tagesson

Forskare

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

Författare

  • Gilberto Pastorello
  • Jonas Ardö
  • Marcin Jackowicz-Korczynski
  • Frans-Jan Parmentier
  • Norbert Pirk
  • Torbern Tagesson
  • Dario Papale

Summary, in English

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.

Avdelning/ar

  • Institutionen för naturgeografi och ekosystemvetenskap
  • BECC: Biodiversity and Ecosystem services in a Changing Climate
  • MERGE: ModElling the Regional and Global Earth system

Publiceringsår

2020

Språk

Engelska

Publikation/Tidskrift/Serie

Scientific Data

Volym

7

Issue

1

Dokumenttyp

Artikel i tidskrift

Förlag

Nature Publishing Group

Ämne

  • Other Earth and Related Environmental Sciences

Nyckelord

  • article
  • breathing
  • ecophysiology
  • ecosystem
  • Eddy covariance
  • licence
  • metadata
  • photosynthesis
  • pipeline
  • remote sensing
  • time series analysis
  • uncertainty

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 2052-4463