This research develops a comparative study between different
multiplicative weights that are assigned to the covariance matrix that
represents the background error in two hybrid assimilation schemes: 3DEnVAR and
4DEnVAR. These weights are distributed between the static and time-invariant
matrix and the matrix generated from the perturbations of a previous ensemble.
The assigned values are 25%, 50%, and 75%, always having as a reference the ensemble matrix. The
experiments are applied to the short-range Prediction System (SisPI) that works
operationally at the Institute of Meteorology. The impact of Tropical Storm Eta
on November 7 and 8, 2020 was selected as a study case. The results suggest
that by giving the main weight to the ensemble matrix more realistic solutions
are achieved because it shows a better representation of the synoptic flow. On
the other hand, it is observed that 3DEnVAR method is more sensitive to
multiplicative weight change of the first guess. More realistic results are
obtained with 50% and 75% relations with 4DEnVAR method, whereas with 3DEnVAR a weight of
75% for the ensemble matrix is required.
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