Speaker: Dr. Benjamin Runkle, Department of Biological and Agricultural Engineering, University of Arkansas

Date: Wednesday, November 4, 2020, 4:00 PM – 5:00 PM

Title: Turbulent time series in micrometeorology: the landscape’s breath

Abstract: My research group uses micrometeorological analysis over environmentally important landscapes to better understand ecological and agricultural practices. We collect the 3D wind vector and gas concentrations (taken about 10 cm apart) at 20 Hz. These time series reveal near-surface atmospheric turbulence as traces left at a single point. One example of the application is in a method called “eddy covariance”. By deriving a covariance between the vertical wind speed and gas concentration, they allow us to generate an estimate of turbulent transport of the gases to and from the surface. Other time series analysis techniques allow more careful attribution of the sources of these gases or effective calculation under more challenging atmospheric conditions. Some examples of the resulting gas flux estimates are the uptake of CO2 in photosynthesis, microbial releases of greenhouse gases, and evaporation of water vapor. There are still many unanswered questions in the process of moving those turbulence data to the transport estimate where collaboration with mathematicians may be especially useful.

Bio: Dr. Runkle is an associate professor of Biological and Agricultural Engineering at the University of Arkansas. He started this position in 2014 following post-doctoral work at the Institute of Soil Science at the University of Hamburg in Germany. He has three degrees in Civil & Environmental Engineering: a B.S.E. from Princeton University and an M.S. and Ph.D. from the University of California, Berkeley. He was awarded an NSF Faculty Early Career Development program grant from the National Science Foundation’s Directorate for Engineering and also has funding from the USDA, USGS, NASA, and the private sector. He researches the terrestrial carbon and water cycles in natural and managed landscapes, and has recently focused on rice production systems in Arkansas. This field-based research involves long-term measurements of key environmental fluxes (e.g., evapotranspiration, surface water flows, and carbon dioxide and methane emissions from the landscape to the atmosphere) and provides the basis for process studies and computer modeling approaches to environmental systems.

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