What can we learn from drones? Addressing the in-situ data gap in meteorology
University of Kentucky
Abstract
The atmospheric boundary layer is where most of the exchange between the Earth’s surface and the atmosphere occurs. It regulates energy transfer, affecting surface temperatures and atmospheric stability with much of these effects introduced amplified through the actions of turbulence which is produced within the boundary layer. This turbulent transport therefore impacts a diverse range of applications including low-level aviation, wind energy, and pollutant dispersion. However, there are not many measurement systems capable of measuring atmospheric boundary layer turbulence and other physical processes that can occur within its boundary layer, resulting in a loss of information referred to as the in-situ data gap. Over the last decade, there has been an increasing interest in using uncrewed aerial vehicles (UAVs) to fill this data gap for both research and operational applications. In this talk, I will discuss the ongoing work being conducted at the University of Kentucky to develop and deploy UAVs for atmospheric research and discuss how UAVs have the potential to become part of operational day-to-day weather forecasting.
About the speaker
Dr. Sean Bailey earned a doctorate at the University of Ottawa funded by both national and provincial scholarships to study the turbulent interactions between rotating flows and turbulence. This was followed by a post-doctoral fellowship and associate research scholarship at Princeton University contributing to research on high Reynolds number turbulence in wall-bounded flows. He joined the Department of Mechanical Engineering at the University of Kentucky in 2010 where he continued his research in the experimental study of turbulent flows with focus on the role of coherent structures in boundary layers, unsteady vortex flows, interaction between coherent structures and homogeneous turbulence, scaling of wall-bounded flows at high Reynolds numbers and the development of experimental methods. In 2014 he received an NSF CAREER award to fund research into using autonomous uncrewed aerial vehicles (UAVs) to measure turbulence in the atmospheric boundary layer and has since deployed UAVs in studies addressing a broad range of atmospheric flows including boundary layer turbulence, drainage flows, wind turbine wakes, and stratospheric turbulence.
