Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 21, issue 20
Articles | Volume 21, issue 20
https://doi.org/10.5194/acp-21-15589-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-21-15589-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 21, issue 20
Technical note
 | 
18 Oct 2021
Technical note |  | 18 Oct 2021

Technical note: Uncertainties in eddy covariance CO2 fluxes in a semiarid sagebrush ecosystem caused by gap-filling approaches

Jingyu Yao, Zhongming Gao, Jianping Huang, Heping Liu, and Guoyin Wang

Viewed

Total article views: 1,401 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
989 378 34 1,401 14 22
  • HTML: 989
  • PDF: 378
  • XML: 34
  • Total: 1,401
  • BibTeX: 14
  • EndNote: 22
Views and downloads (calculated since 28 Jul 2021)
Cumulative views and downloads (calculated since 28 Jul 2021)

Viewed (geographical distribution)

Total article views: 1,401 (including HTML, PDF, and XML) Thereof 1,395 with geography defined and 6 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 25 Mar 2023
Download
Short summary
Gap-filling usually accounts for a large source of uncertainties in the annual CO2 fluxes, though gap-filling CO2 fluxes is challenging at dryland sites due to small fluxes. Using data collected from a semiarid site, four machine learning methods are evaluated with different lengths of artificial gaps. The artificial neural network and random forest methods outperform the other methods. With these methods, uncertainties in the annual CO2 flux at this site are estimated to be within 16 g C m−2.
Read more
Altmetrics
Final-revised paper
Preprint