Forecasting skill of model averages

Given a collection of science-based computational models that all estimate states of the same environmental system, we compare the forecast skill of the average of the collection to the skills of the individual members. We illustrate our results through an analysis of regional climate model data and give general criteria for the average to perform more or less skillfully than the most skillful individual model, the "best" model. The average will only be more skillful than the best model if the individual models in the collection produce very different forecasts; if the individual forecasts generally agree, the average will not be as skillful as the best model.

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This is a preprint of an article submitted for consideration in Stochastic Environmental Research and Risk Assessment. The final publication is available at www.springerlink.com
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Author Winter, Larry
Nychka, Douglas
Publisher UCAR/NCAR - Library
Publication Date 2010-07-01T00:00:00
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Topic Category geoscientificInformation
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Metadata Date 2025-07-17T15:25:09.983692
Metadata Record Identifier edu.ucar.opensky::articles:10352
Metadata Language eng; USA
Suggested Citation Winter, Larry, Nychka, Douglas. (2010). Forecasting skill of model averages. UCAR/NCAR - Library. https://n2t.org/ark:/85065/d7ws8tp2. Accessed 02 August 2025.

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