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The purpose of the present study is to use a new method of empirical model error correction, developed by Danforth et al. (2007) , based on estimating the systematic component of the non-periodic errors linearly dependent on the anomalous state. The method uses Singular Value Decomposition (SVD) to generate a basis of model errors and states. It requires only a time series of errors to estimate covariances and uses negligible additional computation during a forecast integration. As a result, itdoi:10.1175/2007jas2419.1 fatcat:gh3ijnzwizgjleuzdhdo4theoa