Addressing Interdependency in a Multi-Model Ensemble

Tuesday, May 13, 2014 - 07:00
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The collection of Earth System Models available in the CMIP5 archive represents, at least to some degree, a sample uncertainty of future climate evolution. The presence of duplicated code in the multiple models in the archive raises at least three potential problems; biases in the mean and variance, the overestimation of sample size and the potential for spurious correlations to emerge in the archive due to model replication. Analytical evidence is presented to demonstrate that the distribution of models in the CMIP5 archive is not consistent with a random sample, and a weighting scheme is proposed to address model co-dependency. A methodology is proposed for selecting diverse and skillful subsets of models in the archive which could be used for impact studies in cases where physically consistent joint projections of multiple variables (and their temporal and spatial characteristics) are required but not available from probabilistic Bayesian methods.