EAGER: A New Aerial Platform for Turbulence Measurements in the Atmospheric Surface Layer

University Of Virginia Main Campus, Charlottesville VA

Investigators

Abstract

This project seeks to advance research in the measurement of winds. Why is it important? Having refined measurements of winds improves weather forecasting. For instance, if we can better predict how winds behave during disaster situations such as wildfires and train derailments that involve toxic gas pollution, we can forecast the behavior and impact of wind factors in local areas and prevent or minimize health risks to the public. This would allow better coordination of emergency response and resources and minimize the economic impact at the local, state, and national levels. To achieve these goals, drone technology will be used in this project. One major benefit of drones is that they can access locations in the atmosphere near the ground that are unsafe to humans or difficult to access otherwise, such as mountainous terrain, lakes, and glaciers. Another benefit of drone technology is that a drone can hover over difficult terrain for a long time, allowing data collection to develop and test wind forecasting models. This type of in-person research in difficult terrain is currently impossible or very difficult to achieve, which has resulted in major weaknesses in wind behavior understanding and in wind forecasting models. Collecting wind data with drones is not only very novel, but also cost-effective. The wind collection technology using drones would address the current research weaknesses and help protect the public in their daily lives or in emergency situations. The project aims to explore the ability of commercial off-the-shelf (COTS) multirotor drones to measure turbulence. The approach is innovative because it only relies on the use of easily retrievable data from COTS drones. There is no need for custom-built frames and tuning of flight control parameters, making the approach cost-efficient and easily accessible to the scientific community without an engineering and/or technical background. The major goals are to investigate 1) the accuracy of these drone-based turbulence measurements, and 2) the dependency of the accuracy on drone size and weight. Measurements will be performed next to a large array of start-of-the-art sonic anemometers over flat terrain in the NSF funded M2HATS field study, offering an unprecedented opportunity for an intercomparison experiment. Eight multi-rotor vehicles will be used, including two different types of COTS multirotor drones to retrieve data necessary to estimate turbulence. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.