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A global carbon assimilation system using a modified ensemble Kalman filter.

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