Comparisons of the Second-Moment Statistics of Climate Models

Kwano-Y. Kim Climate System Research Program, Texas A&M University, College Station, Texas

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Gerald R. North Climate System Research Program, Texas A&M University, College Station, Texas

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Gabriele C. Hegerl Max-Planck-Institut für Meteorologie, Hamburg, Germany

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Abstract

In this study the magnitude and the temporal and spatial correlation scales of background fluctuations generated by three climate models, two different coupled ocean-atmosphere general circulation models and one energy balance model, were examined. These second-moment statistics of the models were compared with each other and with those of the observation data in several frequency bands. This exercise shows some discordance between the models and the observations and also significant discrepancy among different numerical models. The authors also calculated the empirical orthogonal functions and eigenvalues because these am important ingredients for formulating estimation and detection algorithms. There are significant model to model variations both in the shape of eigenfunctions and in the spectrum of eigenvalues. Also, consistency between the modeled eigenfunctions and eigenvalues and those of the observations are rather poor, especially in the low-frequency bands.

Abstract

In this study the magnitude and the temporal and spatial correlation scales of background fluctuations generated by three climate models, two different coupled ocean-atmosphere general circulation models and one energy balance model, were examined. These second-moment statistics of the models were compared with each other and with those of the observation data in several frequency bands. This exercise shows some discordance between the models and the observations and also significant discrepancy among different numerical models. The authors also calculated the empirical orthogonal functions and eigenvalues because these am important ingredients for formulating estimation and detection algorithms. There are significant model to model variations both in the shape of eigenfunctions and in the spectrum of eigenvalues. Also, consistency between the modeled eigenfunctions and eigenvalues and those of the observations are rather poor, especially in the low-frequency bands.

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