Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 13, issue 5
Articles | Volume 13, issue 5
https://doi.org/10.5194/gmd-13-2297-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-2297-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 5
Model evaluation paper
 | 
15 May 2020
Model evaluation paper |  | 15 May 2020

Representing model uncertainty for global atmospheric CO2 flux inversions using ECMWF-IFS-46R1

Joe R. McNorton, Nicolas Bousserez, Anna Agustí-Panareda, Gianpaolo Balsamo, Margarita Choulga, Andrew Dawson, Richard Engelen, Zak Kipling, and Simon Lang

Supplement

https://doi.org/10.5194/gmd-13-2297-2020-supplement

Data sets

Representing Model Uncertainty for Global Atmospheric CO2 Flux Inversions Using ECMWF-IFS-46R1 J. McNorton, N. Bousserez, A. Agustí-Panareda, G. Balsamo, M. Choulga, A. Dawson, R. Engelen, Z. Kipling, and S. Lang https://doi.org/10.5281/zenodo.3750842

Model code and software

Representing Model Uncertainty for Global Atmospheric CO2 Flux Inversions Using ECMWF-IFS-46R1 J. McNorton, N. Bousserez, A. Agustí-Panareda, G. Balsamo, M. Choulga, A. Dawson, R. Engelen, Z. Kipling, and S. Lang https://doi.org/10.5281/zenodo.3750842

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Short summary
To infer carbon emissions from observations using atmospheric models, detailed knowledge of uncertainty is required. The uncertainties associated with models are often estimated because they are difficult to attribute. Here we use a state-of-the-art weather model to assess the impact of uncertainty in the wind fields on atmospheric concentrations of carbon dioxide. These results can be used to help quantify the uncertainty in estimated carbon emissions from atmospheric observations.
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