On the optimisation of RBF-based radar rainmap prediction

The problem of analysing and forecasting the motion of rain structures sensed by weather radar is mostly faced using approaches based on correlation of rain intensity values. Some approaches, however, consider rain structures as a base for the analysis. Of such approaches we considered a neural RBF-based one, of which we recently presented an improved version. The method we develop shows advantages over a linear prediction, while on the other side it is heavy and thus requires some tuning of the parameters to avoid exceedingly long processing times. In this paper we present some facts we discovered about time-saving compromises in tuning parameters and provide some rule-of-thumb guidelines for selecting their values.