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.