Turbulence Awareness via Real-Time Data Mining

Automatic Dependent Surveillance - Broadcast (ADS-B) has been mandated by the FAA for all aircraft that fly in Class A airspace in year 2020 and beyond. ADS-B will be the foundation of surveillance, and in this SBIR effort, we exploit the fact thta ADS-B data can also provide evidence of aircraft flying through known sources of aviation turbulence. Phase I R&D showed that moderate or greater levels of turbulence can be identified by analyzing in real-time certain key features observable from ADS-B data. Mountain wave turbulence, clear air turbulence, and convective induced turbulence events can all be identified from the data mining approach that we have developed. Analysis results can be performed in near real time and in an automated fashion, and can trigger safety alerts on AOC dispatcher displays or can be used to build better turbulence forecasts and nowcasts.