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Geosci. Model Dev., 9, 2999-3026, 2016
https://doi.org/10.5194/gmd-9-2999-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Development and technical paper
02 Sep 2016
Constraining a land-surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System V1.0
Gregor J. Schürmann et al.
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Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version      Supplement - Supplement
 
RC1: 'Review of "Constraining a land surface model with multiple observations by application of the MPI-Carbon Cycle Data Assimilation System"', Anonymous Referee #1, 23 Feb 2016 Printer-friendly Version 
AC2: 'Reply to RC1', Gregor Schürmann, 24 Jun 2016 Printer-friendly Version Supplement 
 
RC2: 'MPI carbon cycle data assimilation system', Anonymous Referee #2, 27 Apr 2016 Printer-friendly Version 
AC3: 'Reply to RC2', Gregor Schürmann, 24 Jun 2016 Printer-friendly Version Supplement 
 
RC3: 'Interesting but manuscript needs work', Anonymous Referee #3, 11 May 2016 Printer-friendly Version Supplement 
AC4: 'Reply to RC3', Gregor Schürmann, 24 Jun 2016 Printer-friendly Version Supplement 
 
AC1: 'Modifications to the manuscript', Gregor Schürmann, 24 Jun 2016 Printer-friendly Version Supplement 
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Gregor Schürmann on behalf of the Authors (11 Jul 2016)  Author's response  Manuscript
ED: Publish subject to minor revisions (Editor review) (19 Jul 2016) by Jatin Kala  
AR by Gregor Schürmann on behalf of the Authors (02 Aug 2016)  Author's response  Manuscript
ED: Publish subject to technical corrections (03 Aug 2016) by Jatin Kala  
CC BY 4.0
Publications Copernicus
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Short summary
We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The system improves the modelled carbon cycle of the terrestrial biosphere by systematically confronting (or assimilating) the model with observations of atmospheric CO2 and fractions of absorbed photosynthetically active radiation. Jointly assimilating both data streams outperforms the single-data stream experiments, thus showing the value of a multi-data stream assimilation.
We describe the Max Planck Institute Carbon Cycle Data Assimilation System (MPI-CCDAS). The...
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