An automatic and effective parameter optimization method for model tuning

Zhang, T.; Li, L.; Lin, Y.; Xue, W.; Xie, F.; Xu, H.; Huang, X.

doi:https://doi.org/10.5194/gmd-8-3579-2015

Articles | Volume 8, issue 11

https://doi.org/10.5194/gmd-8-3579-2015

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

Special issue:

Community software to support the delivery of CMIP5

https://doi.org/10.5194/gmd-8-3579-2015

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

Articles | Volume 8, issue 11

Development and technical paper

|

06 Nov 2015

Development and technical paper |

| 06 Nov 2015

An automatic and effective parameter optimization method for model tuning

T. Zhang, L. Li, Y. Lin, W. Xue, F. Xie, H. Xu, and X. Huang

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Final revised paper (published on 06 Nov 2015)
Preprint (discussion started on 07 May 2015)

Interactive discussion

Status: closed

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

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- Supplement

RC C973: 'Review of T. Zhang et al.', Anonymous Referee #1, 04 Jun 2015
- AC C1087: 'Reply to Referee #1', Tao Zhang, 15 Jun 2015
RC C1336: 'Review comments of the manuscript entitled “An automatic and effective parameter optimization method for model tuning” by T. Zhang, L. Li, Y. Lin, W. Xue, F. Xie, H. Xu, and X. Huang', Anonymous Referee #2, 10 Jul 2015

Peer-review completion

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

AR by Tao Zhang on behalf of the Authors (27 Aug 2015) Author's response

ED: Publish subject to technical corrections (09 Oct 2015) by Richard Neale

AR by Tao Zhang on behalf of the Authors (17 Oct 2015) Author's response Manuscript

Short summary

A “three-step” methodology is proposed to effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. The optimal results improve the metrics performance by 9%. A software framework can automatically execute any part of the “three-step” calibration strategy. The proposed methodology and framework can easily be applied to other GCMs to speed up the model development process.