Some tools for focusing variational data assimilation in ocean modelling

International audienceSome tools are presented, which aim is to concentrate the effect of data assimilation on particular aspects of interest. In a first part, a reduced order approach for 4D-Var data assimilation is described. The control space is defined as the span of a few vectors representing a significant part of the system variability. It is shown that such an approach can lead to significant improvements, both in terms of the quality of the solution and of the computational efficiency, with regard to data assimilation with a full control vector. However this approach presents also several limitations. In particular, the choice and the evolution of the reduced basis are discussed. In a second part, we address the problem of variational data assimilation for nested models. An adjoint formulation is derived, and it is shown in particular that assimilation considering the whole multigrid system can lead to improved results with regard to assimilation in the high resolution model only. Examples of applications will be given in the context of ocean modellin