In this master thesis we concentrate on the dynamics of changes in the precipitation intensity through a time sequence of radar images and inspect how this can be used as a parameter in automatic severe weather prediction.
We approach the problem from a topological standpoint and we demonstrate how discrete Morse theory can be used in tracking changes in a sequence of weather images and show how we can follow important features in the given sequence by building bifurcation diagrams.
Our method is evaluated on real data represented as a sequence of weather images taken by a weather radar. In order to avoid noise and to obtain only those features from the images that are significant to our research, we also implement a method for reducing noise.
At the end we present a simple model for classification of the bifurcation diagrams and show how the bifurcation diagrams and the amount of precipitation intensity could influence prediction of weather phenomena.