Natural cloud seeding refers to the process by which snow particles are produced at higher levels in the atmosphere and then fall and impact clouds and precipitation at a lower level. In this award, the impact of natural cloud seeding on lake-effect snowfall in the US Great Lakes will be investigated. The main societal impact of the project will be through the potential for improved forecasting of lake-effect snowfall location and intensity through better choices of numerical weather model parameters. The processes investigated here may also have broader applications, such as to Arctic locations that have increased open water. The project will help to train the next generation of scientists by involving multiple graduate students.
This research is for the analysis of the potential for natural cloud seeding to impact microphysical properties and turbulent storm dynamics in the lake-effect layer. The research will make use of data from the 2013-2014 Ontario Winter Lake-effect Systems (OWLeS) field project, particularly in situ data from the University of Wyoming King Air research aircraft and remote sensing data from the Wyoming Cloud Radar on the King Air and the ground-based Doppler on Wheels radars. Three main scientific objectives will be investigated: 1) Determine the importance of â€œexternalâ€ sources of snow on the microphysical and thermodynamic evolution of lake-effect snowstorms, 2) Determine the impacts of seeding on the lake-effect boundary layer entrainment zone, and 3) Develop a catalog of microphysical and turbulence profiles in lake-effect systems for comparison with environmental conditions.
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.