Articles | Volume 15, issue 15
Research article
04 Aug 2015
Research article |  | 04 Aug 2015

Improvement of climate predictions and reduction of their uncertainties using learning algorithms

E. Strobach and G. Bel

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Subject: Dynamics | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Physics (physical properties and processes)
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Cited articles

Buser, C. M., Künsch, H. R., Lüthi, D., Wild, M., and Schär, C.: Bayesian multi-model projection of climate: bias assumptions and interannual variability, Clim. Dynam., 33, 849–868, 2009.
Buser, C., Künsch, H., and Schär, C.: Bayesian multi-model projections of climate: generalization and application to ENSEMBLES results, Clim. Res., 44, 227–241, 2010.
Cesa-Bianchi, N. and Lugosi, G.: Prediction, Learning, and Games, Cambridge University Press, Cambridge, UK, 2006.
Chakraborty, A. and Krishnamurti, T. N.: Improving global model precipitation forecasts over India using downscaling and the FSU superensemble. Part II: Seasonal climate, Mon. Weather Rev., 137, 2736–2757, 2009.
Collins, M.: Ensembles and probabilities: a new era in the prediction of climate change, Philos. T. R. Soc. A, 365, 1957–1970, 2007.
Final-revised paper