Incremental 4D-Var convergence study

Reduced-order 4D-Var: a preconditioner for the Incremental 4D-Var data assimilation method

This study demonstrates how the incremental 4D-Var data assimilation method can be applied efficiently preconditioned in an application to an oceanographic problem. The approach consists in performing a few iterations of the reduced-order 4D-Var prior to the incremental 4D-Var in the full space in order to achieve faster convergence. An application performed in the tropical Pacific Ocean, with ...

Diagnostics of linear and incremental approximations in 4D-Var revisited for higher resolution analysis

A Study of 4D-Var and EnKF Coupling

34 35 Coupling parameter-estimation (CPE) that uses observations in a medium to 36 estimate the parameters in other media may increase the coherence and consistence of 37 estimated parameters in a coupled system, through the uses of co-varying relationship 38 between variables residing in different media. However, accurately evaluating the 39 strength of co-varying of different media is usually...

Discussion on ‘4D-Var or EnKF?’

The development of data assimilation techniques for numerical weather prediction has been very successful ever since the early 1950s until now, starting with simple two-dimensional and univariate spatial interpolation techniques like the successive corrections (SC, Bergthorsson and Döös, 1955) ending up with the four-dimensional variational data assimilation (4D-Var, Rabier et al., 2000) and en...

SPRINTARS/4D-Var data assimilation system

Introduction Conclusions References