Severe Hail Fall and Hailstorm Detection Using Remote Sensing Observations

Area of Science:

• Atmospheric Science
• Meteorology
• Remote Sensing

Background:

• Severe hail events cause significant property damage in the U.S.
• Ground-based radar (NEXRAD) and geostationary satellites are key tools for severe storm detection.
• Recent upgrades to radar and satellite technology necessitate an updated assessment of their capabilities.

Purpose of the Study:

• To compare the effectiveness of radar and satellite data in identifying hailstorms and hail occurrence.
• To assess the ability of different radar types (single- vs. dual-polarization) to discriminate hail sizes.
• To propose improvements to the Maximum Expected Size of Hail (MESH) metric.

Main Methods:

• Analyzed over 10,000 storms identified via radar echo-top tracking.
• Utilized nearly 6,000 hail reports from 30 severe weather days (2013-present).
• Compared radar (single- and dual-polarization) and satellite observational products.

Main Results:

• Radar observations demonstrated the highest skill in discriminating severe from non-severe hailstorms and identifying hail occurrence.
• Single- and dual-polarization radar performed similarly, but combining metrics yielded the greatest skill.
• Proposed revisions to the MESH metric improved comparisons between reported and estimated hail sizes.

Conclusions:

• Radar remains the most skillful tool for real-time severe hail detection and characterization.
• Combining radar polarization metrics enhances hail detection capabilities.
• Improvements to the MESH metric are crucial for accurate hail size estimation.