Articles | Volume 15, issue 2
https://doi.org/10.5194/acp-15-1087-2015
https://doi.org/10.5194/acp-15-1087-2015
Research article
 | 
30 Jan 2015
Research article |  | 30 Jan 2015

A regional carbon data assimilation system and its preliminary evaluation in East Asia

Z. Peng, M. Zhang, X. Kou, X. Tian, and X. Ma

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Cited articles

Ahmadov, R., Gerbig, C., Kretschmer, R., Körner, S., Rödenbeck, C., Bousquet, P., and Ramonet, M.: Comparing high resolution WRF-VPRM simulations and two global CO2 transport models with coastal tower measurements of CO2, Biogeosciences, 6, 807–817, https://doi.org/10.5194/bg-6-807-2009, 2009.
Andres, R. J., Boden, T. A., Bréon, F.-M., Ciais, P., Davis, S., Erickson, D., Gregg, J. S., Jacobson, A., Marland, G., Miller, J., Oda, T., Olivier, J. G. J., Raupach, M. R., Rayner, P., and Treanton, K.: A synthesis of carbon dioxide emissions from fossil-fuel combustion, Biogeosciences, 9, 1845–1871, https://doi.org/10.5194/bg-9-1845-2012, 2012.
Baker, D. F., Doney, S. C., and Schimel, D. S.: Variational data assimilation for atmospheric CO2, Tellus B, 58, 359–365, 2006.
Boden, T. A., Marland, G., and Andres, R. J.: Global, regional, and national fossil-fuel CO2 emissions, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, US Department of Energy, Oak Ridge, Tenn., USA, https://doi.org/10.3334/CDIAC/00001_V2011, 2011.
Chevallier, F.: Impact of correlated observation errors on inverted CO2 surface fluxes from OCO measurements, Geophys. Res. Lett., 34, L24804, https://doi.org/10.1029/2007GL030463, 2007.
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Short summary
We associated the smoothing operator with the atmospheric transport model to constitute the persistence dynamical model to forecast the surface CO2 flux scaling factors for the purpose of resolving the "signal-to-noise" problem, as well as transporting the useful observed information onto the next assimilation cycle. Based on this improvement, a regional surface CO2 flux inversion system, CFI-CMAQ, has been developed. The OSSEs showed that the performance of CFI-CMAQ is effective and promising.
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