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.

Related authors

An effective parameter optimization with radiation balance constraint in CAM5 (version 5.3)
Li Wu, Tao Zhang, Yi Qin, and Wei Xue
Geosci. Model Dev., 13, 41–53,,, 2020
Short summary
Parameter calibration in global soil carbon models using surrogate-based optimization
Haoyu Xu, Tao Zhang, Yiqi Luo, Xin Huang, and Wei Xue
Geosci. Model Dev., 11, 3027–3044,,, 2018
Short summary
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
Geosci. Model Dev., 8, 3579–3591,,, 2015
Short summary

Related subject area

Climate and Earth system modeling
Impact of increased resolution on the representation of the Canary upwelling system in climate models
Adama Sylla, Emilia Sanchez Gomez, Juliette Mignot, and Jorge López-Parages
Geosci. Model Dev., 15, 8245–8267,,, 2022
Short summary
Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI): protocol and initial results from the first simulations
Jadwiga H. Richter, Daniele Visioni, Douglas G. MacMartin, David A. Bailey, Nan Rosenbloom, Brian Dobbins, Walker R. Lee, Mari Tye, and Jean-Francois Lamarque
Geosci. Model Dev., 15, 8221–8243,,, 2022
Short summary
Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)
Gonzalo A. Ferrada, Meng Zhou, Jun Wang, Alexei Lyapustin, Yujie Wang, Saulo R. Freitas, and Gregory R. Carmichael
Geosci. Model Dev., 15, 8085–8109,,, 2022
Short summary
Impact of physical parameterizations on wind simulation with WRF V3.9.1.1 under stable conditions at planetary boundary layer gray-zone resolution: a case study over the coastal regions of North China
Entao Yu, Rui Bai, Xia Chen, and Lifang Shao
Geosci. Model Dev., 15, 8111–8134,,, 2022
Short summary
Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States
Xingying Huang, Andrew Gettelman, William C. Skamarock, Peter Hjort Lauritzen, Miles Curry, Adam Herrington, John T. Truesdale, and Michael Duda
Geosci. Model Dev., 15, 8135–8151,,, 2022
Short summary

Cited articles

Allen, M. R., Stott, P. A., Mitchell, J. F., Schnur, R., and Delworth, T. L.: Quantifying the uncertainty in forecasts of anthropogenic climate change, Nature, 407, 617–620, 2000. a
Bardenet, R., Brendel, M., Kégl, B., and Sebag, M.: Collaborative hyperparameter tuning, in: paper presented at the 30th International Conference on Machine Learning (ICML-13), 199–207, ACM, Atlanta, USA, 2013. a
Boyle, J., Klein, S., Zhang, G., Xie, S., and Wei, X.: Climate model forecast experiments for TOGA COARE, Mon. Weather Rev., 136, 808–832, 2008. a
Bretherton, C. S. and Park, S.: A new moist turbulence parameterization in the Community Atmosphere Model, J. Climate, 22, 3422–3448, 2009. a
Covey, C., Lucas, D. D., Tannahill, J., Garaizar, X., and Klein, R.: Efficient screening of climate model sensitivity to a large number of perturbed input parameters, J. Adv. Model. Earth Sy., 5, 598–610, 2013. a
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.