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ESD | Articles | Volume 10, issue 1
Earth Syst. Dynam., 10, 91-105, 2019
https://doi.org/10.5194/esd-10-91-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Earth Syst. Dynam., 10, 91-105, 2019
https://doi.org/10.5194/esd-10-91-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

ESD Reviews 13 Feb 2019

ESD Reviews | 13 Feb 2019

ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing

Gab Abramowitz et al.
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Cited articles  
Abramowitz, G.: Model independence in multi-model ensemble prediction, Aust. Meteorol. Ocean., 59, 3–6, 2010. 
Abramowitz, G. and Gupta, H.: Toward a model space and model independence metric, Geophys. Res. Lett., 35, L05705, https://doi.org/10.1029/2007GL032834, 2008. 
Abramowitz, G. and Bishop, C. H.: Climate Model Dependence and the Ensemble Dependence Transformation of CMIP Projections, J. Climate, 28, 2332–2348, 2015. 
Annan, J. D. and Hargreaves, J. C.: Reliability of the CMIP3 ensemble, Geophys. Res. Lett., 37, L02703, https://doi.org/10.1029/2009GL041994, 2010. 
Annan, J. D. and Hargreaves, J. C.: Understanding the CMIP3 ensemble, J. Climate, 24, 4529–4538, 2011. 
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Best estimates of future climate projections typically rely on a range of climate models from different international research institutions. However, it is unclear how independent these different estimates are, and, for example, the degree to which their agreement implies robustness. This work presents a review of the varied and disparate attempts to quantify and address model dependence within multi-model climate projection ensembles.
Best estimates of future climate projections typically rely on a range of climate models from...
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