Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 17, issue 14
Articles | Volume 17, issue 14
https://doi.org/10.5194/gmd-17-5619-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-5619-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 17, issue 14
Model description paper
 | 
25 Jul 2024
Model description paper |  | 25 Jul 2024

EAT v1.0.0: a 1D test bed for physical–biogeochemical data assimilation in natural waters

Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta

Viewed

Total article views: 2,770 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,983 670 117 2,770 151 198
  • HTML: 1,983
  • PDF: 670
  • XML: 117
  • Total: 2,770
  • BibTeX: 151
  • EndNote: 198
Views and downloads (calculated since 21 Dec 2023)
Cumulative views and downloads (calculated since 21 Dec 2023)

Viewed (geographical distribution)

Total article views: 2,770 (including HTML, PDF, and XML) Thereof 2,770 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

Latest update: 16 May 2026
Download
Short summary
To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through data assimilation which blends numerical models and observations. We present the Ensemble and Assimilation Tool (EAT), a flexible and efficient test bed that allows any scientist to explore and further develop the state of the art in data assimilation.
Read more
Share