A global carbon assimilation system using a modified ensemble Kalman filter

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

doi:https://doi.org/10.5194/gmd-8-805-2015

Articles | Volume 8, issue 3

https://doi.org/10.5194/gmd-8-805-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-8-805-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 8, issue 3

Model description paper

|

25 Mar 2015

Model description paper |

| 25 Mar 2015

A global carbon assimilation system using a modified ensemble Kalman filter

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

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Final revised paper (published on 25 Mar 2015)
Preprint (discussion started on 01 Oct 2014)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC C2208: 'review', Anonymous Referee #1, 05 Nov 2014
- AC C3287: 'Reply to Anonymous Referee #1', S. Zhang, 06 Feb 2015
RC C2648: 'referee comment', Peter Rayner, 12 Dec 2014
- AC C3286: 'Reply to Prof P. Rayner', S. Zhang, 06 Feb 2015

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by S. Zhang on behalf of the Authors (06 Feb 2015) Author's response Manuscript

ED: Referee Nomination & Report Request started (13 Feb 2015) by James Annan

ED: Publish subject to technical corrections (26 Feb 2015) by James Annan

AR by S. Zhang on behalf of the Authors (06 Mar 2015) Author's response Manuscript

Short summary

A Global Carbon Assimilation System based on the Ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is similar to CarbonTracker, but with several new developments. The results showed that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.