Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 2, 137-144, 2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
28 Sep 2009
Bayesian calibration of the Thermosphere-Ionosphere Electrodynamics General Circulation Model (TIE-GCM)
S. Guillas1, J. Rougier2, A. Maute3, A. D. Richmond3, and C. D. Linkletter4 1Department of Statistical Science & Aon Benfield UCL Hazard Research Centre, University College London, London, UK
2Department of Mathematics, University of Bristol, Bristol, UK
3High Altitude Observatory, National Center for Atmospheric Research, Boulder CO, USA
4Center for Statistical Sciences, Brown University, Providence, RI, USA
Abstract. In this paper, we demonstrate a procedure for calibrating a complex computer simulation model having uncertain inputs and internal parameters, with application to the NCAR Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM). We compare simulated magnetic perturbations with observations at two ground locations for various combinations of calibration parameters. These calibration parameters are: the amplitude of the semidiurnal tidal perturbation in the height of a constant-pressure surface at the TIE-GCM lower boundary, the local time at which this maximises and the minimum night-time electron density. A fully Bayesian approach, that describes correlations in time and in the calibration input space is implemented. A Markov Chain Monte Carlo (MCMC) approach leads to potential optimal values for the amplitude and phase (within the limitations of the selected data and calibration parameters) but not for the minimum night-time electron density. The procedure can be extended to include additional data types and calibration parameters.

Citation: Guillas, S., Rougier, J., Maute, A., Richmond, A. D., and Linkletter, C. D.: Bayesian calibration of the Thermosphere-Ionosphere Electrodynamics General Circulation Model (TIE-GCM), Geosci. Model Dev., 2, 137-144,, 2009.
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