Efficient Formulation and Implementation of Data Assimilation Methods

Abstract

This Special Issue presents efficient formulations and implementations of sequential and variational data assimilation methods. The methods address three important issues in the context of operational data assimilation: efficient implementation of localization methods, sampling methods for approaching posterior ensembles under non-linear model errors, and adjoint-free formulations of four dimensional variational methods.

Keywords

• ensemble Kalman filter
• posterior ensemble
• modified Cholesky decomposition
• sampling methods
• empirical orthogonal functions
• Gaussian mixture models