Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 10
Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2995-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-2995-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 10
Development and technical paper
 | 
31 May 2023
Development and technical paper |  | 31 May 2023

Testing the reconstruction of modelled particulate organic carbon from surface ecosystem components using PlankTOM12 and machine learning

Anna Denvil-Sommer, Erik T. Buitenhuis, Rainer Kiko, Fabien Lombard, Lionel Guidi, and Corinne Le Quéré

Viewed

Total article views: 2,380 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,500 788 92 2,380 98 157
  • HTML: 1,500
  • PDF: 788
  • XML: 92
  • Total: 2,380
  • BibTeX: 98
  • EndNote: 157
Views and downloads (calculated since 18 Nov 2022)
Cumulative views and downloads (calculated since 18 Nov 2022)

Viewed (geographical distribution)

Total article views: 2,380 (including HTML, PDF, and XML) Thereof 2,341 with geography defined and 39 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 06 Dec 2025
Download
Short summary
Using outputs of global biogeochemical ocean model and machine learning methods, we demonstrate that it will be possible to identify linkages between surface environmental and ecosystem structure and the export of carbon to depth by sinking organic particles using real observations. It will be possible to use this knowledge to improve both our understanding of ecosystem dynamics and of their functional representation within models.
Read more
Share