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A global carbon assimilation system using a modified ensemble Kalman filter.
- Source :
- Geoscientific Model Development; 2015, Vol. 8 Issue 3, p805-816, 12p
- Publication Year :
- 2015
-
Abstract
- A Global Carbon Assimilation System based on the ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO<subscript>2</subscript> data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO<subscript>2</subscript> distribution. This assimilation approach is similar to CarbonTracker, but with several new developments, including inclusion of atmospheric CO<subscript>2</subscript> 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<subscript>2</subscript> 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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1991959X
- Volume :
- 8
- Issue :
- 3
- Database :
- Complementary Index
- Journal :
- Geoscientific Model Development
- Publication Type :
- Academic Journal
- Accession number :
- 101895575
- Full Text :
- https://doi.org/10.5194/gmd-8-805-2015