MICHAEL BUBAN, Ph.D.
Duties:
Research Scientist
Programs:
Atmospheric Modeling and
Surface-Layer Meteorology
Contact:
michael.buban@noaa.gov
Office: (405) 210-6085
Current Research
Current research interests include investigating land-atmosphere interaction and the role of surface heterogeneity on cumului development, convection initiation and boundary layer structure, hydrodynamic stability of shear flows, the dynamics of mesoscale boundary layer circulations, and the formation of discrete small-scale atmospheric vortices.
For more information on my research click here.
A listing of publications is available in pdf format here.
Education
University of Oklahoma, Norman, OK
Ph.D., Meteorology, 2014
M.S., Meteorology, 2005
Northern Illinois University, DeKalb, IL
B.S. Meteorology, 2001
Professional Experience
Research Scientist, Cooperative Institute for Mesoscale Meteorological Studies, Norman, OK working in-residence at the NOAA Air Resources Laboratory, Atmospheric Turbulence and Diffusion Division, Oak Ridge, TN
2017 to Present
Postdoctoral Research Associate, NOAA Air Resources Laboratory, Atmospheric Turbulence and Diffusion Division, Oak Ridge, TN
2016 to 2017
Postdoctoral Research Associate, Earth System Science Interdisciplinary Center, University of Maryland
NOAA Air Resources Laboratory, Atmospheric Turbulence and Diffusion Division, Oak Ridge, TN
2015 to 2016
Michael and Tom Wood prepare to launch
a weather balloon.
Michael, Temple Lee, and Ed Dumas prepare the unmanned aerial system (otherwise known as the “octocopter”) for flight testing.
More about my research
In addition to Current Research mentioned above I’m also involved in:
- Running Large Eddy Simulations to test sensitivities of boundary layer circulations, cloud formation, and low-level vorticity production on surface fluxes, soil properties, and vegetation characteristics with a goal of improving parameterizations in NWP models;
- Using small Unmanned Aircraft Systems (sUAS) to profile the atmospheric boundary layer;
- Using the US Climate reference network (USCRN) to improve the national water model.