Flying Safe in Dallas–Fort Worth—Meeting the Weather-Alerting Needs of Drone and Air Taxi Operators

Future drone and air taxi services will take place in the lowest parts of the atmosphere – a region vastly under-sampled by weather radar across the nation and under-served by profilers and other in-situ sensors. This leads to a lack of situational awareness of changing weather conditions at these heights, bringing uncertainty to aerial ride sharing, cargo delivery and emergency services, impacting up-time, business viability and safety. This presentation discusses these challenges from a user perspective and presents solutions currently being prototyped to keep drone and air taxi services safe in the face of changing weather.

The focus of this presentation is North Central Texas, a growing home for drone and air taxi operations, with several organizations planning to debut major commercial services and with public agencies already conducting routine operations in support of public safety. In collaboration with the North Central Texas Council of Governments, the CASA Engineering Research Center has been working closely with public and private agencies in the region to prototype, demonstrate and operationalize severe weather (hail, tornadoes, flooding) observation and alerting technologies. This includes a network of X-band weather radars in the Dallas Fort Worth metroplex that look close to the ground (0-2000 feet AGL) and a severe weather alerting technology that can provide users contextually-relevant, location dependent and customized weather information.

This presentation presents the results of interviews with drone and air taxi operators, discussing their needs (and current sources) for weather information, and presents an integrated (sensors-to-alerting) solution that is being prototyped and demonstrated in the region in collaboration with local universities, government agencies, local airports and the local National Weather Service Weather Forecast Office. The presentation will also discuss how the alerting solution developed here could be integrated into the UTM system.