Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 18, issue 1
Articles | Volume 18, issue 1
https://doi.org/10.5194/amt-18-241-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-241-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 1
Research article
 | 
15 Jan 2025
Research article |  | 15 Jan 2025

Retrieving the atmospheric concentrations of carbon dioxide and methane from the European Copernicus CO2M satellite mission using artificial neural networks

Maximilian Reuter, Michael Hilker, Stefan Noël, Antonio Di Noia, Michael Weimer, Oliver Schneising, Michael Buchwitz, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang

Data sets

Complete ERA5 from 1940: Fifth generation of ECMWF atmospheric reanalyses of the global climate H. Hersbach et al. https://doi.org/10.24381/cds.143582cf

MODIS/Terra+Aqua BRDF/AlbedoModel Parameters Daily L3 Global 0.05Deg CMG V061 C. Schaaf and Z. Wang https://doi.org/10.5067/MODIS/MCD43C1.061

MODIS/Aqua Vegetation Indices Monthly L3 Global 0.05Deg CMG V061 K. Didan https://doi.org/10.5067/MODIS/MYD13C2.061

The CAMS reanalysis of atmospheric composition (https://ads.atmosphere.copernicus.eu/datasets/cams-global-reanalysis-eac4) Antje Inness et al. https://doi.org/10.5194/acp-19-3515-2019

Inferring CO2 sources and sinks from satellite observations: Method and application to TOVS data (https://ads.atmosphere.copernicus.eu/datasets/cams-global-greenhouse-gas-inversion) F. Chevallier et al. https://doi.org/10.1029/2005jd006390

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Short summary
Carbon dioxide (CO2) and methane (CH4) are the main anthropogenic greenhouse gases. The European Copernicus CO2 monitoring satellite mission CO2M will provide measurements of their atmospheric concentrations, but the accuracy requirements are demanding and conventional retrieval methods computationally expensive. We present a new retrieval algorithm based on artificial neural networks that has the potential to meet the stringent requirements of the CO2M mission with minimal computational effort.
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