During the past 20 years there has been great success in understanding and detecting microbursts. These "traditional" wind shear events are most prominent in the summer and are characterized by a two-dimensional, divergent outflow associated with precipitation loading from a thunderstorm downdraft or evaporative cooling from high-based rain clouds. Analysis of wind shear loss alerts at the Dallas/Fort Worth International Airport (DFW) from August 1999 through July 2002 reveals that a significant number of the wind shear events were generated by "non-traditional" mechanisms. The "non-traditional" wind shear mechanisms, linear divergence, divergence behind gust fronts, and gravity waves, accounted for one half of the alert events in the period studied. Radar-based algorithms have shown considerable skill in detecting wind shear events. However, the algorithms were developed to identifl features common to the "traditional" events. If the algorithms were modified to detect "non-traditional" wind shear, the corresponding increase in false detections could be unacceptable. Therefore, in this report a new radar-based algorithm is proposed that detects linear divergence, divergence behind gust fronts, and gravity waves for output on the Integrated Terminal Weather System by identifying the radar signatures that are common to these features.