Articles | Volume 10, issue 6
https://doi.org/10.5194/gmd-10-2379-2017
https://doi.org/10.5194/gmd-10-2379-2017
Methods for assessment of models
 | 
28 Jun 2017
Methods for assessment of models |  | 28 Jun 2017

Skill and independence weighting for multi-model assessments

Benjamin M. Sanderson, Michael Wehner, and Reto Knutti

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Cited articles

Abramowitz, G. and Bishop, C. H.: Climate model dependence and the ensemble dependence transformation of cmip projections, J. Climate, 28, 2332–2348, 2015.
Alexander, L., Donat, M., Takayama, Y., and Yang, H.: The climdex project: creation of long-term global gridded products for the analysis of temperature and precipitation extremes, WCRP Open Science conference, Denver, 2011.
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Aumann, H. H., Chahine, M. T., Gautier, C., Goldberg, M. D., Kalnay, E., McMillin, L. M., Revercomb, H., Rosenkranz, P. W., Smith, W. L., Staelin, D. H., and Strow, L. L.: AIRS/AMSU/HSB on the Aqua Mission: Design, Science Objectives, Data Products, and Processing Systems, IEEE T. Geosci. Remote, 41, 253–264, https://doi.org/10.1109/TGRS.2002.808356, 2003.
Bishop, C. H. and Abramowitz, G.: Climate model dependence and the replicate earth paradigm, Clim. Dynam., 41, 885–900, 2013.
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Short summary
How should climate model simulations be combined to produce an overall assessment that reflects both their performance and their interdependencies? This paper presents a strategy for weighting climate model output such that models that are replicated or models that perform poorly in a chosen set of metrics are appropriately weighted. We perform sensitivity tests to show how the method results depend on variables and parameter values.
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