F. Bouttier, THE DYNAMICS OF ERROR COVARIANCES IN A BAROTROPIC MODEL, Tellus. Series A, Dynamic meteorology and oceanography, 45A(5), 1993, pp. 408-423
Under the hypothesis of linear error growth, the tangent linear model
can be used to provide a simplified form of stochastic-dynamic predict
ion, in which the uncertainty on a model forecast is defined by the er
ror covariances between the model state variables. We apply this metho
d on a global vorticity equation model with a simple initial condition
for the covariance matrix. The forecast error variances and correlati
ons undergo rapid modifications in relation with the atmospheric flow
pattern. This may have some implications for operational assimilation
schemes in numerical weather prediction. A deeper understanding of the
relevant processes is sought, using an adjoint form of the prediction
equation, in order to assess the impact of the initial variances and
correlations, and of the intrinsic dynamics of the model flow. The app
lication on some simplified flows shows the relevance of diffusion, ad
vection, Rossby wave dispersion and barotropic instability to forecast
skill prediction.