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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Development and technical paper
31 Jan 2017
Review status
A revision of this discussion paper was accepted for the journal Geoscientific Model Development (GMD) and is expected to appear here in due course.
Calibrating Climate Models Using Inverse Methods: Case studies with HadAM3, HadAM3P and HadCM3
Simon F. B. Tett1, Kuniko Yamazaki1,2, Michael J. Mineter1, Coralia Cartis3, and Nathan Eizenberg3,4 1School of Geosciences, University of Edinburgh, Crew Building, Alexander Crum Brown Road, The King’s Buildings, Edinburgh EH9 3FF, UK
2Met Office, Fitzroy Road, Exeter, Devon, EX1 3PB, UK
3Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, UK
4Bureau of Meteorology, GPO Box 1289, Melbourne, VIC 3001, Australia
Abstract. Optimisation methods were successfully used to calibrate parameters in an atmospheric component of a climate model using two variants of the Gauss-Newton line-search algorithm. 1) A standard Gauss-Newton algorithm in which, in each iteration, all parameters were perturbed. 2) A randomized block-coordinate variant in which, in each iteration, a random sub-set of parameters was perturbed. The cost function to be minimized used multiple large-scale observations and was constrained to produce net radiative fluxes close to those observed. These algorithms were used to calibrate the HadAM3 (3rd Hadley Centre Atmospheric Model) model at N48 resolution and the HadAM3P model at N96 resolution.

For the HadAM3 model, cases with seven and fourteen parameters were tried. All ten 7-parameter cases using HadAM3 converged to cost function values similar to that of the standard configuration. For the 14-parameter cases several failed to converge, with the random variant in which 6 parameters were perturbed being most successful. Multiple sets of parameter values were found that produced multiple models very similar to the standard configuration. HadAM3 cases that converged were coupled to an ocean model and ran for 20 years starting from a pre-industrial HadCM3 (3rd Hadley Centre Coupled model) state resulting in several models whose global-average temperatures were consistent with pre-industrial estimates. For the 7-parameter cases the Gauss-Newton algorithm converged in about 70 evaluations. For the 14-parameter algorithm with 6 parameters being randomly perturbed about 80 evaluations were needed for convergence. However, when 8 parameters were randomly perturbed algorithm performance was poor. Our results suggest the computational cost for the Gauss-Newton algorithm scales between P and P2 where P is the number of parameters being calibrated.

For the HadAM3P model three algorithms were tested. Algorithms in which seven parameters were perturbed and three out of seven parameters randomly perturbed produced final configurations comparable to the standard hand tuned configuration. An algorithm in which six out of thirteen parameters were randomly perturbed failed to converge.

These results suggest that automatic parameter calibration using atmospheric models is feasible and that the resulting coupled models are stable. Thus, automatic calibration could replace human driven trial and error. However, convergence and costs are, likely, sensitive to details of the algorithm.

Citation: Tett, S. F. B., Yamazaki, K., Mineter, M. J., Cartis, C., and Eizenberg, N.: Calibrating Climate Models Using Inverse Methods: Case studies with HadAM3, HadAM3P and HadCM3, Geosci. Model Dev. Discuss.,, in review, 2017.
Simon F. B. Tett et al.
Simon F. B. Tett et al.
Simon F. B. Tett et al.


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Publications Copernicus
Short summary
The paper shows it is possible to automatically calibrate the parameters in the atmospheric component of a climate model. The resulting atmosphere/ocean models are often, but not always, stable and realistic. The computational cost to do this is feasible. The implications are that it is possible to generate multiple configurations of a single model with different parameter values but which all look similar to the standard model and that the techniques could be used to calibrate other models.
The paper shows it is possible to automatically calibrate the parameters in the atmospheric...