We conjecture that this is because the bred vectors collapse as they “age” into a subspace which is too small: the stochastic perturbations due to nonlinearity and convection, etc., are not enough to avoid this collapse. As a result, some directions of growing errors are missed. In order to avoid this problem, we added random perturbations to the bred vectors at the beginning of the 12- hr integrations. This reduced by 40% the errors with the global bred vectors (Corazza et al 2002). With the Ott et al (2002) local bred vector Kalman Filtering approach the improvements are even more dramatic.