Forecasting skill of model averages

AMS Citation:
Winter, C. L., and D. Nychka, 2010: Forecasting skill of model averages. Stochastic Environmental Research and Risk Assessment, 24, 633-638, doi:10.1007/s00477-009-0350-y.
Date:2010-07-01
Resource Type:article
Title:Forecasting skill of model averages
Abstract: 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.
Subject(s):Model average, Model comparison, Environmental models, Mean-square error, Stochastic processes, Uncertainty
Peer Review:Refereed
Copyright Information: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
OpenSky citable URL: ark:/85065/d7ws8tp2
Publisher's Version: 10.1007/s00477-009-0350-y
Author(s):
  • C. Winter - NCAR/UCAR
  • Doug Nychka - NCAR/UCAR
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