Our faculty serve dual roles as rigorous researchers and professional teachers. Faculty research has been published in peer-reviewed journals such as Monthly Weather Review and International Journal of Climatology.
David SiutaResearch Scientist
B.S. Earth System Science – University of Wyoming (2011)
M.S. Atmospheric Science – University of Wyoming (2013)
Ph.D. Atmospheric Science – University of British Columbia (2017)
Professional Interests and Activities
Dr. David Siuta joined the Lyndon State Atmospheric Sciences department as a Research Scientist in Fall 2017. He comes to Lyndon State after completing his PhD at the University of British Columbia, where he studied the use of numerical weather prediction forecasts for wind energy in mountainous topography. For his dissertation, Dr. Siuta showed the sensitivities of hub-height wind-speed forecasts produced using the Weather Research and Forecasting (WRF) model to boundary-layer physics choice, successfully developed a method to produce reliable probabilistic forecasts, and derived new similarity relationships describing wind profiles over vegetated mountain ridges. He also pioneered efforts on the use of cloud-computing services for real-time numerical weather prediction. At Lyndon State, Dr. Siuta will apply his knowledge to research snowfall and ice storm prediction in Vermont with Dr. Jason Shafer.
Dr. Siuta is originally from central New Jersey, but has also lived in Wyoming and British Columbia. One of his favorite annual activities is hiking Colorado’s high mountain peaks during the summer. After moving to Vermont, he is looking forward to exploring many of the northeast’s hiking, biking, and running opportunities.
Siuta, D., West, G., Modzelewski, H., Schigas, R., & Stull, R. (2016). Viability of Cloud Computing for Real-Time Numerical Weather Prediction. Weather and Forecasting, 31(6), 1985–1996. http://doi.org/10.1175/WAF-D-16-0075.1
Siuta, D., West, G., & Stull, R. (2017). WRF Hub-Height Wind-Forecast Sensitivity to PBL Scheme, Grid Length, and Initial-Condition Choice in Complex Terrain. Weather and Forecasting. http://doi.org/10.1175/WAF-D-16-0120.1