This post is also available in: עברית (Hebrew)
Micro weather forecasting is essential with drone deliveries and air taxi operations. With most UAS weighing less than 55 pounds, even mild gusts of wind could disrupt their flight. Especially in metropolitan areas, where tall buildings can create unpredictable weather forces, more sophisticated forecasting software is needed to ensure that aircraft can operate both safely and efficiently.
Researchers at Embry-Riddle Aeronautical University flew small unmanned aircraft systems (sUAS) along simulated delivery routes in Florida. The exercise proved the viability of the hyperlocal weather-prediction tools needed to fly autonomous systems in populated areas.
The research endeavors to filter weather data from the National Oceanic and Atmospheric Administration (NOAA) and nearby ground stations through 3D models of urban environments to refine forecasts to specific locations.
The team’s General Urban area Microclimate Predictions tool (GUMP) leverages machine learning and Computational Fluid Dynamics (CFD) simulations to convert computer wind flow fields into an intuitive risk map for drone operators, according to erau.edu.