This project will involve continued assessment of the potential impacts of aerosol pollution and natural dust sources on severe convective storms and mesoscale convective systems (MCSs). Prior research by this investigator based upon the Regional Atmospheric Modeling System (RAMS) model has suggested that dust-aerosol influences could significantly influence the evolution of storm outbreaks in the central plains and (ultimately) alter the potential for tornadogenesis within individual convective storms, while other research has pointed to possible aerosol influences on hail formation. To further pursue these topics the research team will focus three key areas, each contributing to the intellectual merit of this effort:
* Assessing aerosol/dust influences on tornadogenesis: Using RAMS version 4.3.0, the researchers will assess the direct radiative effects of dust on the environmental thermodynamic profile with special attention to the "capping inversion," the ability of dust serving as nuclei to alter supercell thunderstorm dynamics, and conduct simulations of actual storm events with attention to assessing impacts of ingested dust.
* Modeling hail formation using a triple-moment cloud microphysical scheme: The researchers will further modify a newly developed triple moment scheme, perform additional sensitivity tests, and simulate one or more real-world cases.
* Assessing aerosol influences on MCSs and hailstorms: The researchers will examine how the variability of cloud condensation nuclei (CCN) concentrations may impact hail formation and size under various environmental conditions, and perform simulations of several observed MCSs that evidently ingested highly polluted air to determine if there are significant feedbacks of ingested CCN on overall storm dynamics and microphysics.
Broader impacts of this research will include the participation of multiple graduate students in the outlined research activities. Modeling resources developed under the grant will be made available to the scientific community via their ultimate inclusion in the Weather Research and Forecasting (WRF) model. The work ultimately has the potential for societal benefits through improved forecasts of severe convective weather events.
