Understanding Hailstone Temporal Variability and Contributing Factors over the U.S. Southern Great Plains

Area of Science:

• Atmospheric Science
• Meteorology
• Climate Science

Background:

• Hail poses a significant natural hazard in the U.S., causing substantial economic losses.
• Understanding hail formation and size is crucial for weather prediction and policymaking.
• Temporal and spatial analysis of severe hail is essential for mitigation strategies.

Purpose of the Study:

• To analyze temporal and spatial variabilities of severe hail in the U.S. Southern Great Plains (SGP) from 2004-2016.
• To investigate the correlation between hail occurrences and factors like sea surface temperature, ENSO, and aerosol loading.
• To identify key drivers of interannual hail variability in the SGP region.

Main Methods:

• Utilized hail reports from the Storm Prediction Center and radar-retrieved Maximum Expected Size of Hail (MESH) data.
• Analyzed temporal and spatial patterns of severe hail occurrences over the SGP states.
• Performed statistical correlation analysis with sea surface temperature anomalies, ENSO, and aerosol loading, identifying and excluding an outlier year (2016).

Main Results:

• Severe hail occurrences in the SGP exhibit significant year-to-year variability.
• Interannual hail variability strongly correlates with sea surface temperature anomalies in the northern Gulf of Mexico.
• Excluding the 2016 outlier, aerosols (potentially from northern Mexico) showed the highest correlation with hail variability, while meteorological covariation did not significantly contribute.

Conclusions:

• Aerosol loading appears to be a significant factor influencing interannual hail variability in the SGP.
• The influence of El Niño-Southern Oscillation (ENSO) and meteorological covariation on hail variability is less robust.
• Further research is warranted to investigate the specific impacts of aerosols on hail formation and occurrence.