| ABSTRACT
In
meteorology the weather analysis can provide a reference against which one
can check the quality of observations. The analysis can be reduced to an interpolation
problem, if the model state is overdetermined by the observations. For the
under-determined problem it is not a straight forward how to perform analysis
because data is sparse and only indirectly related to the model variables.
In order to solve the problem we need to rely on some background information
in the form of a priori estimate of the model state, where any physical constrains
on the analysis can be helpful. One of the ways to approach this problem is
through applying the data assimilation method to it. In this talk I will try
to present some basic theory which goes with the DA method and illustrate it
on an example.
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