A global carbon assimilation system using a modified ensemble Kalman filter Academic Article uri icon

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abstract

  • <p><strong>Abstract.</strong> A Global Carbon Assimilation System based on the ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO<sub>2</sub> data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO<sub>2</sub> distribution. This assimilation approach is similar to CarbonTracker, but with several new developments, including inclusion of atmospheric CO<sub>2</sub> concentration in state vectors, using the ensemble Kalman filter (EnKF) with 1-week assimilation windows, using analysis states to iteratively estimate ensemble forecast errors, and a maximum likelihood estimation of the inflation factors of the forecast and observation errors. The proposed assimilation approach is used to estimate the terrestrial ecosystem carbon fluxes and atmospheric CO<sub>2</sub> distributions from 2002 to 2008. The results show that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.</p>

authors

  • Zhang, S
  • Zheng, X
  • Chen, Jing
  • Chen, Z
  • Dan, B
  • Yi, X
  • Wang, L
  • Wu, G

publication date

  • January 1, 2015