Articles | Volume 2, issue 1
18 Apr 2016
 | 18 Apr 2016

Building a traceable climate model hierarchy with multi-level emulators

Giang T. Tran, Kevin I. C. Oliver, András Sóbester, David J. J. Toal, Philip B. Holden, Robert Marsh, Peter Challenor, and Neil R. Edwards

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Cited articles

Castruccio, S., McInerney, D. J., Stein, M. L., Crouch, F. L., Jacob, R. L., and Moyer, E. J.: Statistical emulation of climate model projections based on precomputed GCM runs, J. Climate, 27, 1829–1844, 2014.
Challenor, P. G., McNeall, D., and Gattiker, J.: Assessing the probability of rare climate events, in: The Oxford handbook of applied bayesian analysis, edited by O'Hagan, A. and West, M., chap. 16, 403–430, Oxford University Press, New York, 2010.
Conti, S. and O'Hagan, A.: Bayesian emulation of complex multi-output and dynamic computer models, J. Stat. Plan. Infer., 140, 640–651,, 2010.
Cook, R. D. and Nachtsheim, C. J.: A comparison of algorithms for constructing exact D-optimal designs, Technometrics, 22, 315–324, 1980.
Cumming, J. and Goldstein, M.: Small Sample Designs for Complex High-Dimensional Models Based on Fast Approximations, Technometrics, 51, 377–388, 2008.
Short summary
In this work, we combine the information from a complex and a simple atmospheric model to efficiently build a statistical representation (an emulator) of the complex model and to study the relationship between them. Thanks to the improved efficiency, this process is now feasible for complex models, which are slow and costly to run. The constructed emulator provide approximations of the model output, allowing various analyses to be made without the need to run the complex model again.