Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.154 IF 5.154
  • IF 5-year value: 5.697 IF 5-year
    5.697
  • CiteScore value: 5.56 CiteScore
    5.56
  • SNIP value: 1.761 SNIP 1.761
  • IPP value: 5.30 IPP 5.30
  • SJR value: 3.164 SJR 3.164
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 59 Scimago H
    index 59
  • h5-index value: 49 h5-index 49
GMD | Articles | Volume 11, issue 11
Geosci. Model Dev., 11, 4489–4513, 2018
https://doi.org/10.5194/gmd-11-4489-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 11, 4489–4513, 2018
https://doi.org/10.5194/gmd-11-4489-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Development and technical paper 09 Nov 2018

Development and technical paper | 09 Nov 2018

On the impact of recent developments of the LMDz atmospheric general circulation model on the simulation of CO2 transport

Marine Remaud et al.

Related authors

Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions
Frédéric Chevallier, Marine Remaud, Christopher W. O'Dell, David Baker, Philippe Peylin, and Anne Cozic
Atmos. Chem. Phys., 19, 14233–14251, https://doi.org/10.5194/acp-19-14233-2019,https://doi.org/10.5194/acp-19-14233-2019, 2019
Short summary

Related subject area

Atmospheric Sciences
Development of a reduced-complexity plant canopy physics surrogate model for use in chemical transport models: a case study with GEOS-Chem v12.3.0
Sam J. Silva, Colette L. Heald, and Alex B. Guenther
Geosci. Model Dev., 13, 2569–2585, https://doi.org/10.5194/gmd-13-2569-2020,https://doi.org/10.5194/gmd-13-2569-2020, 2020
Short summary
An adaptive method for speeding up the numerical integration of chemical mechanisms in atmospheric chemistry models: application to GEOS-Chem version 12.0.0
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Xuan Wang, and Wei Chen
Geosci. Model Dev., 13, 2475–2486, https://doi.org/10.5194/gmd-13-2475-2020,https://doi.org/10.5194/gmd-13-2475-2020, 2020
Short summary
Satellite-derived leaf area index and roughness length information for surface–atmosphere exchange modelling: a case study for reactive nitrogen deposition in north-western Europe using LOTOS-EUROS v2.0
Shelley C. van der Graaf, Richard Kranenburg, Arjo J. Segers, Martijn Schaap, and Jan Willem Erisman
Geosci. Model Dev., 13, 2451–2474, https://doi.org/10.5194/gmd-13-2451-2020,https://doi.org/10.5194/gmd-13-2451-2020, 2020
Short summary
An online emission module for atmospheric chemistry transport models: implementation in COSMO-GHG v5.6a and COSMO-ART v5.1-3.1
Michael Jähn, Gerrit Kuhlmann, Qing Mu, Jean-Matthieu Haussaire, David Ochsner, Katherine Osterried, Valentin Clément, and Dominik Brunner
Geosci. Model Dev., 13, 2379–2392, https://doi.org/10.5194/gmd-13-2379-2020,https://doi.org/10.5194/gmd-13-2379-2020, 2020
Short summary
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
Geosci. Model Dev., 13, 2297–2313, https://doi.org/10.5194/gmd-13-2297-2020,https://doi.org/10.5194/gmd-13-2297-2020, 2020
Short summary

Cited articles

Basu, S., Baker, D. F., Chevallier, F., Patra, P. K., Liu, J., and Miller, J. B.: The impact of transport model differences on CO2 surface flux estimates from OCO-2 retrievals of column average CO2, Atmos. Chem. Phys., 18, 7189–7215, https://doi.org/10.5194/acp-18-7189-2018, 2018. a, b
Belikov, D. A., Maksyutov, S., Krol, M., Fraser, A., Rigby, M., Bian, H., Agusti-Panareda, A., Bergmann, D., Bousquet, P., Cameron-Smith, P., Chipperfield, M. P., Fortems-Cheiney, A., Gloor, E., Haynes, K., Hess, P., Houweling, S., Kawa, S. R., Law, R. M., Loh, Z., Meng, L., Palmer, P. I., Patra, P. K., Prinn, R. G., Saito, R., and Wilson, C.: Off-line algorithm for calculation of vertical tracer transport in the troposphere due to deep convection, Atmos. Chem. Phys., 13, 1093–1114, https://doi.org/10.5194/acp-13-1093-2013, 2013. a
Byrne, B., Jones, D. B. A., Strong, K., Zeng, Z., Deng, F., and Liu, J.: Sensitivity of CO2 surface flux constraints to observational coverage, J. Geophys. Res.-Atmos., 122, 6672–6694, https://doi.org/10.1002/2016JD026164, 2017. a
Chevallier, F.: Validation report for the inverted CO2 fluxes, v15r4, Report, Copernicus Atmosphere Monitoring Service, 2017. a, b, c
Chevallier, F., Engelen, R. J., and Peylin, P.: The contribution of AIRS data to the estimation of CO2 sources and sinks, Geophys. Res. Lett., 32, L23801, https://doi.org/10.1029/2005GL024229, 2005. a
Publications Copernicus
Download
Short summary
We compare several versions of a global atmospheric transport model for the simulation of CO2. The representation of subgrid-scale processes modulates the interhemispheric gradient and the amplitude of the seasonal cycle in the Northern Hemisphere. It has the largest impact over Brazil. Refining the horizontal resolution improves the simulation near emission hotspots or along the coastlines. The sensitivities to the land surface model and to the increase in vertical resolution are marginal.
We compare several versions of a global atmospheric transport model for the simulation of CO2....
Citation