In Corazza et al, 2002, we showed that the use of the
standard 3D-Var error covariance matrix augmented with
global bred vectors reduced by about 20% the analysis
However, when we added random errors (as if they were
observation errors) to the bred vector at the beginning of
each integration, the analysis errors were much smaller,
more than 40% smaller than the regular 3D-Var.
We conjecture that this is because, in the standard
breeding approach (Toth and Kalnay, 1993, 1997), the
bred vectors tend to collapse into a subspace which is too