Articles | Volume 8, issue 2
https://doi.org/10.5194/esd-8-429-2017
https://doi.org/10.5194/esd-8-429-2017
Research article
 | 
28 Jun 2017
Research article |  | 28 Jun 2017

An efficient training scheme for supermodels

Francine J. Schevenhoven and Frank M. Selten

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Cited articles

Branicki, M. and Majda, A. J.: An Information-Theoretic Framework for Improving Imperfect Dynamical Predictions Via Multi-Model Ensemble Forecasts, J. Nonlinear Sci., 25, 489–538, https://doi.org/10.1007/s00332-015-9233-1, 2015.
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Short summary
Weather and climate models have improved steadily over time, but the models remain imperfect. Given these imperfect models, predictions might be improved by combining the models into a so-called “supermodel”. In this paper we show a new method to construct such a supermodel. The results indicate that the supermodel has superior forecast quality compared to the individual models.
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