Articles | Volume 20, issue 3
https://doi.org/10.5194/os-20-689-2024
https://doi.org/10.5194/os-20-689-2024
Research article
 | 
27 May 2024
Research article |  | 27 May 2024

Combining neural networks and data assimilation to enhance the spatial impact of Argo floats in the Copernicus Mediterranean biogeochemical model

Carolina Amadio, Anna Teruzzi, Gloria Pietropolli, Luca Manzoni, Gianluca Coidessa, and Gianpiero Cossarini

Viewed

Total article views: 2,411 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,926 413 72 2,411 82 97
  • HTML: 1,926
  • PDF: 413
  • XML: 72
  • Total: 2,411
  • BibTeX: 82
  • EndNote: 97
Views and downloads (calculated since 19 Jul 2023)
Cumulative views and downloads (calculated since 19 Jul 2023)

Viewed (geographical distribution)

Total article views: 2,411 (including HTML, PDF, and XML) Thereof 2,341 with geography defined and 70 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 26 Nov 2025
Download
Short summary
Forecasting of marine biogeochemistry can be improved via the assimilation of observations. Floating buoys provide multivariate information about the status of the ocean interior. Information on the ocean interior can be expanded/augmented by machine learning. In this work, we show the enhanced impact of assimilating new in situ variables (oxygen) and reconstructed variables (nitrate) in the operational forecast system (MedBFM) model of the Mediterranean Sea.
Share