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Preprints
https://doi.org/10.5194/essd-2016-36
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/essd-2016-36
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  23 Aug 2016

23 Aug 2016

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This preprint has been withdrawn by the authors.

Understanding the representativeness of FLUXNET for upscaling carbon flux from eddy covariance measurements

Jitendra Kumar1, Forrest M. Hoffman2, William W. Hargrove3, and Nathan Collier2 Jitendra Kumar et al.
  • 1Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
  • 2Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA
  • 3Eastern Forest Environmental Threat Assessment Center, USDA Forest Service, Asheville, NC, USA

Abstract. Eddy covariance data from regional flux networks are direct in situ measurement of carbon, water, and energy fluxes and are of vital importance for understanding the spatio-temporal dynamics of the the global carbon cycle. FLUXNET links regional networks of eddy covariance sites across the globe to quantify the spatial and temporal variability of fluxes at regional to global scales and to detect emergent ecosystem properties. This study presents an assessment of the representativeness of FLUXNET based on the recently released FLUXNET2015 data set. We present a detailed high resolution analysis of the evolving representativeness of FLUXNET through time. Results provide quantitative insights into the extent that various biomes are sampled by the network of networks, the role of the spatial distribution of the sites on the network scale representativeness at any given time, and how that representativeness has changed through time due to changing operational status and data availability at sites in the network. To realize the full potential of FLUXNET observations for understanding emergent ecosystem properties at regional and global scales, we present an approach for upscaling eddy covariance measurements. Informed by the representativeness of observations at the flux sites in the network, the upscaled data reflects the spatio-temporal dynamics of the carbon cycle captured by the in situ measurements. This study presents a method for optimal use of the rich point measurements from FLUXNET to derive an understanding of upscaled carbon fluxes, which can be routinely updated as new data become available, and direct network expansion by identifying regions poorly sampled by the current network.

Data from this study are available at http://dx.doi.org/10.15486/NGT/1279968

This preprint has been withdrawn.

Jitendra Kumar et al.

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Jitendra Kumar et al.

Data sets

Global 4 km resolution monthly gridded Gross Primary Productivity (GPP) data set derived from FLUXNET2015 Jitendra Kumar, Forrest M. Hoffman, William W. Hargrove, and Nathan Collier https://doi.org/10.15486/NGT/1279968

Jitendra Kumar et al.

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Short summary
The Eddy-covariance measurements from global network of flux sites help understand the emergent ecosystem properties. This study presents an approach to assess the representativeness of the observations at the flux sites and upscale the measured fluxes to develop time series of high resolution global gridded data set. Upscaled gross primary productivity data sets captures the heterogeneity of terrestrial ecosystem and reflects the seasonal and interannual variability observed at flux sites.
The Eddy-covariance measurements from global network of flux sites help understand the emergent...
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