¥ 4D-Var and EnKF are the two advanced,
feasible methods
¥ There will be a workshop on them in
Buenos Aires (NovÕ08)!!!
¥ In Ensemble Kalman Filter the background
error covariance B is approximated and advanced in time with an ensemble of K forecasts. In the subspace of the ensemble, B=I so that matrix inversions are efficient.
¥ So far, comparisons show EnKF is
slightly better than 3D-Var, but there has not been enough time to develop tunings
¥ At JMA, Takemasa Miyoshi has been
performing comparisons of the Local Ensemble Transform Kalman Filter (Hunt et al., 2007) with their operational 4D-Var
¥ Comparisons are made for August 2004