Computational Tools for Data Assimilation

The task of providing an optimal analysis of the state of the atmosphere requires the development of novel computational tools that facilitate an effcient integration of observational data into models.

We introduce variational and statistical estimation approaches to data assimilation. We discuss important computational aspects including the construction of effcient models for background errors, the construction and analysis of discrete adjoint models, new approaches to estimate the information content of observations, and hybrid variational-ensemble approaches to assimilation.

Data assimilation results for several real problems are used to illustrate the power of the proposed methods.