Articles | Volume 11, issue 7
Development and technical paper
27 Jul 2018
Development and technical paper |  | 27 Jul 2018

Parameter calibration in global soil carbon models using surrogate-based optimization

Haoyu Xu, Tao Zhang, Yiqi Luo, Xin Huang, and Wei Xue


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Haoyu Xu on behalf of the Authors (05 Feb 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (06 Feb 2018) by Christoph Müller
RR by Anonymous Referee #1 (04 Mar 2018)
RR by Maarten Braakhekke (05 Mar 2018)
ED: Publish subject to minor revisions (review by editor) (13 Mar 2018) by Christoph Müller
AR by Haoyu Xu on behalf of the Authors (02 May 2018)  Author's response    Manuscript
ED: Publish as is (09 May 2018) by Christoph Müller
Short summary
This study proposes a new parameter calibration method based on surrogate optimization techniques to improve the prediction accuracy of soil organic carbon. Experiments on three popular global soil carbon cycle models show that the surrogate-based optimization method is effective and efficient in terms of both accuracy and cost. This research would help develop and improve the parameterization schemes of Earth climate systems.