This research focuses on investigations of hazardous weather from mesoscale convective systems (MCS). The Principal Investigator will address two research objectives: (1) Modeling studies of the effects of dust and pollution-produced aerosol on severe storms with an emphasis on tornado outbreaks; (2) Implementation of a three-moment hail model and applying it to studies of impacts of aerosol on hail size and severe storm dynamics. Thus, the intellectual merit of the research is that it will explore relationships between aerosols and the severity of convective storms.
The broader impacts involve investigating a causal relationship between dust and storm severity, which potentially could lead to a modification of severe storm forecasting techniques to include aerosol variability. These techniques could include nowcasting of severe weather using satellite-derived dust and pollution products as well as development of a new infrastructure in numerical weather prediction centers for implementation of aerosol physics into models, the retrieval of quantitative aerosol products, and models for dust and pollution sources and transport. This improvement in forecasting could lead to a reduction in storm damage and loss of life. The educational benefit of this research is that results of this work will be immediately incorporated in the course content of first year and advanced courses in cloud physics and cloud dynamics as well as textbooks authored by the Principal Investigator. In addition, the research will provide support for two PhD and one postdoctoral student.
, William R. Cotton, PI, are as follows. This research has shown that human-produced aerosols as well as natural dust can impact severe tornadic storms and hailstorms. Our first idealized three-dimensional study suggested that "other things being the same," a severe storm environment with high concentrations of anthropogenic pollution aerosols or dust is more favorable for tornadogenesis. Those simulations revealed that high aerosol concentrations reduced supercell storm precipitation rates and weakened the strength of cold-pools beneath the storm, which enhanced the coupling between low-level incipient tornadic vorticies and the rotating supercell circulation aloft. However, subsequent simulations revealed that aerosol influences on the likelihood of tornado formation has a much smaller impact compared to the combined effects of low-level moisture and instability in the environment. This project also involved the development of new parameterizations, or computational methods, for activation of both dust and anthropogenic pollution aerosols to form cloud droplets. These computational methods can now be used in high-resolution storm models and can be adapted to operational weather forecasting and climate prediction models. In addition, new parameterizations, or computational methods have been developed for representing hail in numerical storm models. These methods permit the simulation or even prediction of the influences of aerosols on the intensity and size of hail, especially large hail, from severe convective storms. The methods developed in this grant are computationally fast enough that they could be implemented in operational weather forecast and climate models.
