Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 11, issue 12
Articles | Volume 11, issue 12
https://doi.org/10.5194/gmd-11-5189-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-5189-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 11, issue 12
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, Minghua Zhang, Wuyin Lin, Yanluan Lin, Wei Xue, Haiyang Yu, Juanxiong He, Xiaoge Xin, Hsi-Yen Ma, Shaocheng Xie, and Weimin Zheng

Viewed

Total article views: 3,423 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,395 959 69 3,423 394 108 100
  • HTML: 2,395
  • PDF: 959
  • XML: 69
  • Total: 3,423
  • Supplement: 394
  • BibTeX: 108
  • EndNote: 100
Views and downloads (calculated since 03 May 2018)
Cumulative views and downloads (calculated since 03 May 2018)

Viewed (geographical distribution)

Total article views: 3,423 (including HTML, PDF, and XML) Thereof 2,937 with geography defined and 486 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 23 Nov 2024
Download
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.
Read more