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A Global Carbon Assimilation System using a modified EnKF assimilation method
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Abstract. A Global Carbon Assimilation System based on Ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 abundance data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is based on the ensemble Kalman filter (EnKF), but with several new developments, including 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 tested in observing system simulation experiments and then used to estimate the terrestrial ecosystem carbon fluxes and atmospheric CO2 distributions from 2002 to 2008. The results showed that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.
Title: A Global Carbon Assimilation System using a modified EnKF assimilation method
Description:
Abstract.
A Global Carbon Assimilation System based on Ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 abundance data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution.
This assimilation approach is based on the ensemble Kalman filter (EnKF), but with several new developments, including 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 tested in observing system simulation experiments and then used to estimate the terrestrial ecosystem carbon fluxes and atmospheric CO2 distributions from 2002 to 2008.
The results showed that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.
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