Articles | Volume 19, issue 3
https://doi.org/10.5194/bg-19-559-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-19-559-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements
Martijn M. T. A. Pallandt
CORRESPONDING AUTHOR
Department of Biogeochemical Signals, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
Jitendra Kumar
Environmental Sciences Division, Oak Ridge National Laboratory, Oak
Ridge, TN 37831, USA
Marguerite Mauritz
Department of Biological Sciences, The University of Texas at El Paso,
El Paso, TX 79902, USA
Edward A. G. Schuur
Center for Ecosystem Science and Society, and Department of Biological
Sciences, Northern Arizona University, Flagstaff, AZ 86011, USA
Anna-Maria Virkkala
Woodwell Climate Research Center, Falmouth, MA 02540, USA
Gerardo Celis
Agronomy Department, University of Florida, Gainesville, FL 32601, USA
Forrest M. Hoffman
Computer Science and Engineering Division, Oak Ridge National
Laboratory, Oak Ridge, TN 37831, USA
Mathias Göckede
Department of Biogeochemical Signals, Max Planck Institute for
Biogeochemistry, 07745 Jena, Germany
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Latest update: 13 Dec 2024
Short summary
Thawing of Arctic permafrost soils could trigger the release of vast amounts of carbon to the atmosphere, thus enhancing climate change. Our study investigated how well the current network of eddy covariance sites to monitor greenhouse gas exchange at local scales captures pan-Arctic flux patterns. We identified large coverage gaps, e.g., in Siberia, but also demonstrated that a targeted addition of relatively few sites can significantly improve network performance.
Thawing of Arctic permafrost soils could trigger the release of vast amounts of carbon to the...
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