Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 11, issue 7
Articles | Volume 11, issue 7
https://doi.org/10.5194/gmd-11-3027-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-11-3027-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 3.0 License.
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

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Latest update: 20 Nov 2024
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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.
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