Articles | Volume 10, issue 6
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.
Annan, J. D. and Hargreaves, J. C.: Understanding the CMIP3 multimodel ensemble, J. Climate, 24, 4529–4538, 2011.
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,, 2003.
Bishop, C. H. and Abramowitz, G.: Climate model dependence and the replicate earth paradigm, Clim. Dynam., 41, 885–900, 2013.
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.