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Green Version.pdf

essd-11-1263-2019.pdf
Preview of Green Version
🔗 Source: earth-syst-sci-data.net
📊 Size: 9 MB
📄 Pages: 27 pages
⬇️ Downloads: 102

Summary

Researchers created a monthly gridded data product of northern wetland methane emissions by upscaling eddy covariance observations using a random forest machine-learning technique. The model was developed using data from 25 sites from 2005 to 2016 and predicted emissions for 2013 and 2014. The performance of the model was evaluated using a leave-one-site-out cross-validation scheme, resulting in a Nash-Sutcliffe model efficiency of 0.47. The annual emissions for northern wetlands were estimated to be 32, 31, or 38 Tg(CH4) yr−1, depending on the wetland distribution map used. The upscaled CH4 flux data products were compared to output from two process models, and methodological issues related to CH4 flux upscaling were discussed. The monthly upscaled CH4 flux data products are available online.

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Researchers created a monthly gridded data product of northern wetland methane emissions by upscaling eddy covariance observations using a random forest...

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  • File Format: PDF
  • File Size: 9 MB
  • Pages: 27
  • Language: EN
  • Total Downloads: 102
  • Last Updated: 5 hours ago

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