Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 9
Articles | Volume 19, issue 9
https://doi.org/10.5194/gmd-19-3757-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-3757-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 9
Model description paper
 | 
08 May 2026
Model description paper |  | 08 May 2026

A novel cluster-based learning scheme to design optimal networks for atmospheric greenhouse gas monitoring (CRO2A version 1.0)

David Matajira-Rueda, Charbel Abdallah, and Thomas Lauvaux

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Short summary
This study presents a scheme, Concepteur de Réseaux Optimaux d’Observations Atmosphériques (CRO2A), for designing optimal mesoscale atmospheric monitoring networks without relying on typical inverse modeling assumptions. It leverages direct simulations of greenhouse gas concentrations to minimize the number of ground-based monitoring stations and maximize network performance through automated processing at a balanced computational cost, while being compatible with high-performance computing.
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