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    Original Research Papers

    Local eigenvalue analysis of CMIP3 climate model errors

    Authors:

    Mikyoung Jun ,

    Department of Statistics, 3143 TAMU, College Station, TX, US
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    Reto Knutti,

    Institute for Atmospheric and Climate Science, ETH Zurich, CH
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    Douglas W. Nychka

    National Center for Atmospheric Research, PO Box 3000, Boulder, CO, US
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    Abstract

    Of the two dozen or so global atmosphere—ocean general circulation models (AOGCMs), many share parameterizations, components or numerical schemes, and several are developed by the same institutions. Thus it is natural to suspect that some of the AOGCMs have correlated error patterns. Here we present a local eigenvalue analysis for the AOGCM errors based on statistically quantified correlation matrices for these errors. Our statistical method enables us to assess the significance of the result based on the simulated data under the assumption that all AOGCMs are independent. The result reveals interesting local features of the dependence structure of AOGCM errors. At least for the variable and the timescale considered here, the Coupled Model Intercomparison Project phase 3 (CMIP3) model archive cannot be treated as a collection of independent models.We use multidimensional scaling to visualize the similarity of AOGCMs and all-subsets regression to provide subsets of AOGCMs that are the best approximation to the variation among the full set of models.

    How to Cite: Jun, M., Knutti, R. and Nychka, D.W., 2008. Local eigenvalue analysis of CMIP3 climate model errors. Tellus A: Dynamic Meteorology and Oceanography, 60(5), pp.992–1000. DOI: http://doi.org/10.1111/j.1600-0870.2008.00356.x
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      Published on 01 Jan 2008
    Peer Reviewed
     CC BY 4.0
     Accepted on 24 Jun 2008            Submitted on 20 Dec 2007

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