Articles | Volume 11, issue 12
Geosci. Model Dev., 11, 5189–5201, 2018
Geosci. Model Dev., 11, 5189–5201, 2018

Development and technical paper 21 Dec 2018

Development and technical paper | 21 Dec 2018

Automatic tuning of the Community Atmospheric Model (CAM5) by using short-term hindcasts with an improved downhill simplex optimization method

Tao Zhang et al.


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 Tao Zhang on behalf of the Authors (16 Nov 2018)  Author's response    Manuscript
ED: Publish as is (25 Nov 2018) by Patrick Jöckel
Short summary
Tuning of uncertain parameters in global atmospheric general circulation models has extreme computational cost. In this study, we provide an automatic tuning method by combining an auto-optimization algorithm with hindcasts to improve climate simulations in CAM5. The tuning improved the overall performance of a well-calibrated model by about 10 %. The computational cost of the entire auto-tuning procedure is just equivalent to a single 20-year simulation of CAM5.