Correlations of control variables in variational data assimilation

Correlations of control variables in variational data assimilation

Variational Data Assimilation : Optimization and Optimal Control

In the last few years due to a constant increase in the need for more precise forecasting and nowcasting, several important developments have taken place in meteorology directed mainly in two different directions: modeling at either large scale or at smaller scales to include an ever increasing number of physical processes and parametrization of subgrid phenomena and adding new sources of data ...

A review of operational methods of variational and ensemble-variational data assimilation: Ensemble-variational data assimilation

Variational and ensemble methods have been developed separately by various research and development groups and each brings its own benefits to data assimilation. In the last decade or so, various ways have been developed to combine these methods, especially with the aims of improving the background-error covariance matrices and of improving efficiency. The field has become confusing, even to ma...

Variational assimilation of Lagrangian data in oceanography

We consider the assimilation of Lagrangian data into a primitive equation circulation model of the ocean at basin scale. The Lagrangian data are positions of floats drifting at fixed depth. We aim at reconstructing the fourdimensional space-time circulation of the ocean. This problem is solved using the four-dimensional variational technique and the adjoint method. In this problem the control v...

Improved variational methods in statistical data assimilation

Data assimilation transfers information from an observed system to a physically based model system with state variables x(t). The observations are typically noisy, the model has errors, and the initial state x(t0) is uncertain: the data assimilation is statistical. One can ask about expected values of functions 〈G(X)〉 on the path X={x(t0), . . .,x(tm)} of the model state through the observation...