Practical exercises in 4D data assimilation using toy models in MATLAB
This is a set of matlab-based practical exercises that can be used to teach or study how four dimensional data assimilation works in the context of simple models.
The document DA_Practicals.pdf guides you through the various exercises and instructs you how to use the codes.
The codes were originally developed by Lisa Neef but borrow heavily from early versions by Saroja Polavarapu at Environment Canada. The exercises also build upon the wonderful tutorials written by Jeff Anderson (NCAR) for the Data Assimilation Resarch Testbed
Currently this document only covers the perturbed-observation Ensemble Kalman Filter and the Lorenz (1963) model, but it's planned to add more materials with variational assimilation, other sequential ensemble filters, and other simple models, later.