Target identification by dual-polarization radar in an operational environment

Two years ago, the McGill S-band scanning radar has been upgraded to dual-polarization. Since the McGill radar is part of the Canadian network of operational radars, dual-polarization work was focussed on the removal of ground clutter and target identification.

On the clutter removal front, we evaluated whether operational-radar quality data of Doppler velocity and polarization parameters could be used to identify ground clutter. Using a fuzzy-logic based classification scheme, we were able to remove most of the ground targets, to the point where it was virtually impossible for trained personnel to identify ground targets that had not been detected by the algorithm. Target identification of hydrometeors was less stellar, in particular in stratiform precipitation where the melting layer proved to be particularly difficult to detect with a high degree of certainty. This is primarily due to the fact that although the bright band has a clear signature visually, its polarization properties vary considerably with depth, making an automatic classification challenging. Yet, proper target identification is proving to become an important issue, as data assimilation experiments done in parallel illustrate that the proper phase (liquid vs solid) of targets must be supplied to the models for short term forecast of convection to work properly.