Articles | Volume 11, issue 12
Geosci. Model Dev., 11, 5189–5201, 2018
https://doi.org/10.5194/gmd-11-5189-2018
Geosci. Model Dev., 11, 5189–5201, 2018
https://doi.org/10.5194/gmd-11-5189-2018
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.

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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.