Part 6:
Four-Dimensional Data Assimilation
Four dimensional data assimilation is a recent development in modeling techniques, but is not itself a model. The four dimensions in FDDA are the three spacial dimensions and time. Basically, FDDA is a method of inserting observed data into the model at the correct time step while the model is running. A direct insertion causes the model to go into what is called "shock", and is generally bad for any model. So FDDA eases the observed data into the model by "nudging" the data into the correct location and time. This nudging is done by slowly changing the model's values for that location, so that the observed data can be assimilated, or inserted, into the model.
A section on how FDDA is used in Models-3 is included in Session 10 (Temporal and Spatial Distribution of Data).
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