Research

(Updating Soon)

  • Monitoring Eastern South Dakota Wetland Status for Flooding Potential and Regional Climate System Interactions, and the integration of Subgrid-scale wetlands into regional climate modeling and numerical weather prediction frameworks.
  • Assessing and quantifying intrinsic forecast risk in numerical weather prediction models and other predictive frameworks
  • Modeling the effects of agricultural land use change and policy on the North American great plains and Eurasia Grain Belt
  • vent-based numerical weather prediction and the impact of assimilating high-speed/abridged data on resulting forecasts
  • Integrating remotely derived Great Lakes lake-surface temperatures into mesoscale models to predict wintertime lake-effect snow.
  • Investigating the applicability of GRID-based technologies towards hydrometeorological and water quality problem domains across the Great Plains Network
  • Contextualizing undergraduate math curricula for meteorology programs by showing the connections between the Trig, Algebra, and Calculus courses they take and our atmospheric sciences curriculum.
  • Exploring and Teaching Scientific Visualization methods in Geosciences and Beyond. And exploring the role of the Internet in disseminating and exploiting geospatial data for research applications.
  • Exploring the potential for Carbon Sequestration practices in South Dakota. Also modeling potential carbon sequestration and Conservation Reserve Program practices to mitigate regional flooding and sediment loading.
  • Coupled Atmospheric and Surface & Groundwater Hydrologic Modeling .
  • Examining the effects that scaling and resolution issues have on the integration remotely derived parameters into subgrid-scale land surface and planetary boundary layer schemes.
  • Modeling biocomplexity processes at interface between the biosciences and geosciences.
  • Examining the effects that image resolution and observations from different platforms have on the remote sensing of surface moisture availability, fractional vegetation cover and energy fluxes. The method used in this study is a thermal infrared/NDVI method interpreted through a Soil-Vegetation-Atmosphere model