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Acknowledgement:

Please acknowledge the use of CAMS data as stated in the CAMS license agreement or Copernicus licence agreement:

  • "Where the Licensee communicates to the public or distributes or publishes CAMS Information, the Licensee shall inform the recipients of the source of that information by using the following or any similar notice:

    'Generated using Copernicus Atmosphere Monitoring Service Information [Year]'.

  • Where the Licensee makes or contributes to a publication or distribution containing adapted or modified CAMS Information, the Licensee shall provide the following or any similar notice:

    'Contains modified Copernicus Atmosphere Monitoring Service Information [Year]';

Any such publication or distribution shall state that "neither the European Commission nor ECMWF is responsible for any use that may be made of the information it contains."

References:


You also might want to reference this paper which describes the global CO2 CAMS data in more detail:

  • Agustí-Panareda, A., Diamantakis, M., Massart, S., Chevallier, F., Muñoz-Sabater, J., Barré, J., Curcoll, R., Engelen, R., Langerock, B., Law, R. M., Loh, Z., Morguí, J. A., Parrington, M., Peuch, V.-H., Ramonet, M., Roehl, C., Vermeulen, A. T., Warneke, T., and Wunch, D.: Modelling CO2 weather – why horizontal resolution matters, Atmos. Chem. Phys., 19, 7347–7376, https://doi.org/10.5194/acp-19-7347-2019, 2019
  • Agustí-Panareda, A., and Coauthors, 2014: Forecasting global atmospheric CO2Atmos. Chem. Phys., 14, 11959-11983, https://doi.org/10.5194/acp-14-11959-2014
  • Agusti-Panareda, A, S. Massart, F. Chevallier, G. Balsamo, S. Boussetta, E. Dutra, and A. Beljaars, 2016: A biogenic CO2 flux adjustment scheme for the mitigation of large-scale biases in global atmospheric CO2 analyses and forecasts, ECMWF Technical Memorandum 773, 37 pp., https://doi.org/10.21957/ylfzoi6i1
  • Agusti-Panareda, A., M. Diamantakis, V. Bayona, F. Klappenbach, and A. Butz, 2017: Improving the inter-hemispheric gradient of total column atmospheric CO2 and CH4 in simulations with the ECMWF semi-Lagrangian atmospheric global model, Geosci. Model Dev., 10, 1-18,  https://doi.org/10.5194/gmd-10-1-2017
  • Massart, S., and Coauthors, 2016: Ability of the 4-D-Var analysis of the GOSAT BESD XCO2 retrievals to characterize atmospheric CO2 at large and synoptic scales, Atmos. Chem. Phys., 16, 1653-1671,https://doi.org/10.5194/acp-16-1653-2016

For CAMS CH4 data please refer to:

  • Agusti-Panareda, A., M. Diamantakis, V. Bayona, F. Klappenbach, and A. Butz, 2017: Improving the inter-hemispheric gradient of total column atmospheric CO2 and CH4 in simulations with the ECMWF semi-Lagrangian atmospheric global model, Geosci. Model Dev., 10, 1-18,  https://doi.org/10.5194/gmd-10-1-2017
  • S. Massart, A. Agusti-Panareda, I. Aben, A. Butz, F. Chevallier, C. Crevoisier, R. Engelen, C. Frankenberg, and O. Hasekamp, 2014:  Assimilation of atmospheric methane products into the MACC-II system: from SCIAMACHY to TANSO and IASI, Atmos. Chem. Phys., 14, 6139-6158, https://doi.org/10.5194/acp-14-6139-2014


On data assimilation for CHEM using the C-IFS (Composition Integrated Forecasting System):

  • Inness, A., and Coauthors, 2015: Data assimilation of satellite-retrieved ozone, carbon monoxide and nitrogen dioxide with ECMWF's Composition-IFS, Atmos. Chem. Phys., 15, 5275-5303, https://doi.org/10.5194/acp-15-5275-2015.


For CO2 and CH4 concentrations from the MACC flux inversion systems, please acknowledge Bergamaschi et al. (2007, 2009) and Chevallier et al. (2010). See the list of the publications documenting the two products below.

  • Bergamaschi, P., and Coauthors, 2007: Satellite chartography of atmospheric methane from SCIAMACHY on board ENVISAT: 2. Evaluation based on inverse model simulations, J. Geophys. Res., 112 , D02304, https://doi.org/10.1029/2006JD007268.
  • Bergamaschi, P., and Coauthors, 2009: Inverse modeling of global and regional CH4 emissions using SCIAMACHY satellite retrievals, J. Geophys. Res., 114, D22301, https://doi.org/10.1029/2009JD012287.
  • Bergamaschi, P., and Coauthors, 2010: Inverse modeling of European CH4 emissions 2001-2006, J. Geophys. Res., 115, D22309, https://doi.org/10.1029/2010JD014180.
  • Bergamaschi, P., and Coauthors, 2013a: Atmospheric CH4 in the first decade of the 21st century: Inverse modeling analysis using SCIAMACHY satellite retrievals and NOAA surface measurements, J. Geophys. Res., 118, 7350-7369, https://doi.org/10.1002/jgrd.50480.
  • Chevallier, F., and Coauthors, 2010: CO2 surface fluxes at grid point scale estimated from a global 21-year reanalysis of atmospheric measurements. J. Geophys. Res., 115, D21307, https://doi.org/10.1029/2010JD013887


For AOD, please refer to:

  • Benedetti, A., and Coauthors, 2009: Aerosol analysis and forecast in the ECMWF Integrated Forecast System. Part II : Data assimilation, J. Geophys. Res., 114, D13205, https://doi.org/10.1029/2008JD011115.
  • Morcrette, and Coauthors, 2009: Aerosol analysis and forecast in the ECMWF Integrated Forecast System. Part I: Forward modelling, J. Geophys. Res., 114, D06206, https://doi.org/10.1029/2008JD011235.


For GFAS, please refer to:

  • Kaiser, J. W., and Coauthors, 2012: Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527-554, https://doi.org/10.5194/bg-9-527-2012.