NSF-SNSF: Flying in Turbulence with UAS

Recent studies reveal that gaps in current atmospheric observations contribute to uncertainties in weather model forecasts. These gaps arise due to a mismatch in resolution between existing measurement tools, such as radiosondes, and modern Numerical Weather Prediction (NWP) models. To address these gaps, this project aims to understand how small Uncrewed Aircraft Systems (sUAS) can obtain high-resolution atmospheric measurements under realistic wind conditions. sUAS offer advantages like reusability and independence from finite resources like helium.

The project will focus on developing a reliable sUAS-based scientific measurement platform for atmospheric data collection and extending the flight autonomy of sUAS through an improved understanding of their interactions with atmospheric turbulence. This initiative will enhance weather forecasts and provide valuable environmental monitoring capabilities.

Spatial and temporal observational gaps in existing measurement systems contribute to model forecast uncertainty. This uncertainty results from a resolution mismatch between current measurement systems, such as radiosondes, and advances in Numerical Weather Predictions (NWPs). This mismatch prevents NWPs from achieving maximum regional skill, particularly for pressure, temperature, humidity, and two-dimensional wind speed and direction measurements.

Considering technological advances in small Uncrewed Aircraft Systems (sUAS) and their deployments for atmospheric boundary layer studies, sUAS could fill this data gap. They provide high-resolution spatiotemporal measurements of the lower atmosphere and maintain ground-relative position even in high winds. Compared to radiosondes, sUAS are nearly 100% reusable, environmentally friendly, and independent of finite resources like helium.

Successful sUAS-based atmospheric measurements date back to the 1970s, with significant advancements in the early 2000s. Research teams developed custom sUAS designs for atmospheric sampling, with publications validating their effectiveness compared to towers, radiosondes, and LIDARs. Recent efforts have shown the feasibility and advantages of assimilating WxUAS data into NWPs and using sUAS for in-situ weather verification.

However, reliable measurements from UAS platforms remain challenging due to the influence of the drone's presence, propulsion unit, and atmospheric turbulence on measurements. Turbulence also reduces flight autonomy and precludes extended missions in turbulent weather. To better understand UAS behavior and capabilities, this project will utilize a pixelated-wind facility known as a windshaper.

Using multifan technology, UAS of any size can be flown in realistic wind conditions, including turbulence, shear flows, gusts, vortical flows, precipitation, and pollution particulates. The two main objectives of the project are: (1) to develop a reliable scientific measurement platform based on UAS for probing atmospheric pollution (chemicals, particulates) and thermodynamic and wind properties, and (2) to extend the flight autonomy of fixed winged UAS by developing a fundamental understanding of their interaction with microscale atmospheric turbulence.

This collaborative U.S.-Swiss project is supported by the U.S. National Science Foundation (NSF) and the Swiss National Science Foundation (SNSF), where NSF funds the U.S. investigator and SNSF funds the partners in Switzerland.

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.