The Weather Systems Processor (WSP) is being deployed by FAA at 35 medium and high-density ASR-9 equipped airports across the United States. The Machine Intelligent Gust Front Algorithm (MIGFA) developed at Lincoln Laboratory provides important gust front detection and tracking capability for this system as well as other FAA systems including Terminal Doppler Weather Radar (TDWR) and Integrated Terminal Weather System (ITWS). The algorithm utilizes multidimensional image processing, data fusion, and fuzzy logic techniques to recognize gust fronts observed in Doppler radar data. Some deficiencies in algorithm performance have been identified through ongoing analysis of data from two initial limited production WSP sites in Austin, TX (AUS) and Albuquerque, NM (ABQ). At AUS, the most common cause of false alarms is bands of low-reflectivity rain echoes having shapes and intensities similar to gust front thin line echoes. Missed or late detections have occasionally occurred when gust fronts are near or embedded in the leading edge of approaching line storms, where direct radar evidence of the gust front (e.g.. thin line echo, velocity convergence) may be fragmented or absent altogether. In ABQ, "canyon wind" events emanating, from mountains located just east of the airport occur with very little lead time, and often with little or no radar signatures, making timely detection on the basis of the radar data alone difficult. MIGFA is equipped with numerous parameters and thresholds that can be adjusted dynamically based on recognition of the local or regional weather context in which it is operating. Through additional contextual weather information processing, this dynamic sensitization capability has been further exploited to address the deficiencies noted above, resulting in an appreciable improvement in performance on data collected at the two WSP sites.