Toward Understanding the Relationship between Aerosol Loadings and Severe Weather Outbreaks across the Great Plains region from 2015-2019

Severe weather is responsible for significant damage to property and loss of life in the United States (USA), especially in the Midwest USA. Forecasting severe weather involves measurements and models of severe weather parameters such as convective available potential energy (CAPE), and bulk shear (change in wind speed and direction with height). However, recent investigations have found that the presence of aerosols (e.g. smoke, dust) can affect severe weather patterns (enhancing or depressing storms) and these effects are not taken into account in the current weather forecasting infrastructure. Therefore, effectively forecasting severe weather outlooks in the presence of aerosols is important to prevent loss of life as well as minimizing economic impacts. This research aims to investigate the relationship (or the lack of relationship) between aerosol loadings in the atmosphere and severe weather outbreaks. We analyze aerosol optical depth (AOD) from MODIS (Terra and Aqua satellites) and VIIRS (Suomi NPP satellite) instruments, observed (balloon sounding) and modeled (North American Regional Reanalysis (NARR)) severe weather parameters such as CAPE and bulk shear, and categorize the data using outlook levels issued by the Storm Prediction Center (SPC). Statistical analyses using probability distribution function techniques are performed to study the relationship between the severe weather parameters and aerosol concentration over the Great Plains region of the USA from 2015-2019 to investigate whether the relationship varies depending on overall favorability/detriment for severe weather.