Biogeosciences
Biogeosciences
BG
Articles | Volume 22, issue 16
Articles | Volume 22, issue 16
https://doi.org/10.5194/bg-22-4061-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-22-4061-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 22, issue 16
Research article
 | 
25 Aug 2025
Research article |  | 25 Aug 2025

Assimilating multi-site eddy-covariance data to calibrate the wetland CH4 emission module in a terrestrial ecosystem model

Jalisha Theanutti Kallingal, Marko Scholze, Paul Anthony Miller, Johan Lindström, Janne Rinne, Mika Aurela, Patrik Vestin, and Per Weslien

Viewed

Total article views: 5,185 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
4,385 602 198 5,185 181 281
  • HTML: 4,385
  • PDF: 602
  • XML: 198
  • Total: 5,185
  • BibTeX: 181
  • EndNote: 281
Views and downloads (calculated since 26 Nov 2024)
Cumulative views and downloads (calculated since 26 Nov 2024)

Viewed (geographical distribution)

Total article views: 5,185 (including HTML, PDF, and XML) Thereof 5,003 with geography defined and 182 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Saved (final revised paper)

Latest update: 03 Jul 2026
Download
Short summary
We explored the possibilities of a Bayesian-based data assimilation algorithm to improve the wetland CH4 flux estimates by a dynamic vegetation model. By assimilating CH4 observations from 14 wetland sites, we calibrated model parameters and estimated large-scale annual emissions from northern wetlands. Our findings indicate that this approach leads to more reliable estimates of CH4 dynamics, which will improve our understanding of the climate change feedback from wetland CH4 emissions.
Read more
Share
Altmetrics
Final-revised paper
Preprint