Thundersnow events (snow attended by lightning and thunder) will be examined with a multiscale approach using standard meteorological platforms (e.g., rawinsonde network, National Lightning Detection Network), observations in the field (integrated sounding system, snow crystal collection), and with numerical model simulations. The project will begin by examining archived cases (1961-1990) of thundersnow to understand the synoptic environment that produces it. Ensuing years will be spent in the field, in pursuit of thundersnow events so that we may sample them directly and attempt to determine some fundamental characteristics of the cloud that engenders them. Direct observations of thundersnow events will reveal not only cloud microphysical structure, but also the stability and vertical velocity profiles that accompany them. Simulations with the Workstation Eta and MASS numerical weather prediction models will help to clarify the synoptic scale and meso-alpha scale forcing mechanisms for vertical motion.
Academically, this project will seek to capitalize on students natural fascination with dangerous phenomena: in this case, lightning and heavy snowfall. Summer workshops will be held for area high school students to introduce them to meteorology and forecasting. Undergraduates at the University of Missouri-Columbia will be introduced to the project in courses taught by the PI (especially their synoptic sequence), with daily forecasting of thundersnow incorporated into the class as a lab exercise. During the winter season, the high school participants from the summer workshop will be invited back to observe the creation by undergraduates of the routine forecasts and outlooks for thundersnow, thus reaching beyond prior summer programs in meteorology for secondary school students. The graduate student participants will venture into the field to perform the observations of thundersnow occurrence. In so doing, they will acquire unique experience in the operation and utility of in-situ rawinsonde and profiler equipment, as well as surface observations and snow crystal collection. These activities will provide the graduate students with the gamut of research experience, from data collection in the field, to quality control in the lab, to the analysis of the final datasets.
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