Articles | Volume 13, issue 5
Geosci. Model Dev., 13, 2297–2313, 2020
https://doi.org/10.5194/gmd-13-2297-2020
Geosci. Model Dev., 13, 2297–2313, 2020
https://doi.org/10.5194/gmd-13-2297-2020

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 et al.

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

Download
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.