Supermodeling for Climate and Weather Prediction

A supermodel is an ensemble of different models in which the models interact with one another in run time. It has been shown that a supermodel can out-perform both the individual models and any average of the model outputs. I will review the supermodeling concept, as presented recently by Frank Selten, with stress on the relationship between supermodeling and data assimilation, as well as the conditions under which supermodeling is better than ex post facto averaging. Finally, I will explain why supermodeling is even more appropriate for short-range weather forecasting than it is for climate projection.

About the presenter
Gregory S. Duane

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FL3-2072 MMM Conf Rm

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Start date and time: 
Friday, August 2, 2013 - 2:30pm