This paper investigates an approach for identification of small-scale precipitation structures within significantly
larger-scale structures in weather radar imaging. The technique utilizes directional smoothing filters to extract
directional information which not apparently observable within large precipitation events. The main goal is to
track these directional characteristics over time, and thus, to predict the overall motion of large structures for
the purpose of forecasting. The objective of this work is not to compete against other weather radar imagingbased
forecasting techniques, but to supplement them. Experimental results illustrate how tracking of directional
structures can be effectively performed.