Since we use the Morss and Emanuel (2001) simulation system, we
know the “truth” and analysis/forecast errors.
We compare the three methods showing
a) the total analysis error for a simulated year over the whole domain,
b) the background error superimposed with the analysis increments.
The 3D-Var parameters have been carefully tuned to get the best
Note that, because it is based on a statistically optimized background
error covariance, 3D-Var cannot capture the “errors of the day”.
The Local Bred Vector Kalman Filtering (Ott et al, 2002) do capture the
errors of the day. However, the bred vectors may “inbreed” to much
and miss some growing directions.
In order to avoid this, we add random perturbations (as if they were
observational errors) to the bred vectors.