A revised scheme to compute horizontal covariances in an oceanographic 3D-VAR assimilation system
We propose an improvement of an oceanographic three dimensional variational assimilation scheme (3D-VAR), named OceanVar, by introducing a recursive filter (RF) with the third order of accuracy (3rd-RF), instead of an RF with first order of accuracy (1st-RF), to approximate horizontal Gaussian covariances. An advantage of the proposed scheme is that the CPU's time can be substantially reduced with benefits on the large scale applications. Experiments estimating the impact of 3rd-RF are performed by assimilating oceanographic data in two realistic oceanographic applications. The results evince benefits in terms of assimilation process computational time, accuracy of the Gaussian correlation modeling, and show that the 3rd-RF is a suitable tool for operational data assimilation.
data assimilation recursive gaussian filter and numerical optimization