A global carbon assimilation system using a modified ensemble Kalman filter

oleh: S. Zhang, X. Zheng, J. M. Chen, Z. Chen, B. Dan, X. Yi, L. Wang, G. Wu

Format: Article
Diterbitkan: Copernicus Publications 2015-03-01

Deskripsi

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.