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Advances in Statistical Climatology, Meteorology and Oceanography An international open-access journal on applied statistics
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Volume 2, issue 1
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 17–37, 2016
https://doi.org/10.5194/ascmo-2-17-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Adv. Stat. Clim. Meteorol. Oceanogr., 2, 17–37, 2016
https://doi.org/10.5194/ascmo-2-17-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  18 Apr 2016

18 Apr 2016

Building a traceable climate model hierarchy with multi-level emulators

Giang T. Tran et al.

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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.
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Conti, S. and O'Hagan, A.: Bayesian emulation of complex multi-output and dynamic computer models, J. Stat. Plan. Infer., 140, 640–651, https://doi.org/10.1016/j.jspi.2009.08.006, 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.
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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.
In this work, we combine the information from a complex and a simple atmospheric model to...
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