By combining satellite data analysis, machine learning technique, and modeling approach, this project will advance our understanding of the long-term impacts of aerosols on convective clouds and lightning through various mechanisms. Understanding aerosol impacts on lightning characteristics such as IC/CG ratio and the fractions of positive CG flash, which contribute to the wildfire ignition and ground damages, is important for the precisely and timely forecast of dangerous lightning flashes.

While we focus on the middle/south central U.S., a typical active thunderstorm region, the integrative analysis proposed herein can be applied to other urban systems. The proposed study is integrated multi-disciplinary in scope by requiring subject-matter knowledge of meteorology, atmospheric chemistry, aerosol-cloud interactions to further NASA’s goals to understand the underlying causality of change through determination of the specific physical processes and mechanisms.