The Radar Echo Classifier for the WSR-88D

A suite of algorithms has been under development for several years that determine the type of scatterer measured by the WSR-88D. This suite of algorithms is termed the Radar Echo Classifier (REC) and uses fuzzy-logic techniques to make this determination. Currently, three algorithms have been designed and tested: the AP Detection Algorithm for anomalously-propagated (AP) ground clutter contamination, the Precipitation Detection Algorithm for convective and stratiform precipitation regions, and the Clear Air Detection Algorithm for return from insects in the boundary layer. Other algorithms can be added to the REC as they are developed.

These algorithms have been tested using data from selected WSR-88D radars and the NCAR S-Pol radar. For the WSR-88D data sets, human experts determine a subjective ``truth'' field for statistical validation of each algorithm. However, for the S-Pol data sets, the dual-polarization data are used to determine the scatterer type through the use of the Particle Identification (PID) algorithm (Vivekanandan et al., 1999). This algorithm includes classifier categories for precipitation particle type, ground clutter, insects and birds. The PID output is used to define the ``truth'' field in an objective sense. Having an objective truth field should improve the quality of the statistical evaluation of algorithm performance. Results from the three REC algorithms will be shown and a statistical evaluation presented. A real-time test of the REC has been achieved at the S-Pol radar during the STEPS field program held during the summer of 2000 in eastern Colorado.

The REC is a planned implementation within the WSR-88D Open Radar Product Generator (ORPG) and is a part of the AP Clutter Mitigation Scheme. The AP Detection Algorithm (APDA) will be implemented first and will be used as a pre-processor of the WSR-88D base data fields prior to input into the Precipitation Processing System (PPS). Eventually, automatic control of the ground clutter filters will be achieved using the output of the APDA to determine where additional clutter filtering is needed. Output from the Precipitation Detection Algorithm (PDA) will be used to determine where compensation of the biased reflectivity that is within precipitation echo will be applied. The reflectivity bias is caused by application of the ground clutter filter.