A 23-Year Severe Hail Climatology Using GridRad MESH Observations

Area of Science:

• Atmospheric Science
• Meteorology
• Climatology

Background:

• Hail report databases have significant biases in size, time, and location, limiting severe hailfall characteristic assessments.
• Previous studies relied on Next Generation Weather Radar (NEXRAD) or reanalysis data, often using limited temporal scales and older versions of the maximum expected size of hail (MESH) parameter.

Purpose of the Study:

• To quantify severe hailfall characteristics over a 23-year period using improved MESH calculations and reanalysis data.
• To develop a corrected hailfall climatology that addresses biases in observational data and accounts for hail reaching the ground.

Main Methods:

• Applied an improved MESH configuration to the GridRad archive (1995-2017) of hourly radar observations.
• Incorporated environmental constraints from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (M2), to filter MESH distributions.
• Analyzed spatial, diurnal, and seasonal patterns of severe hailfall.

Main Results:

• The MESH-only method identified two high-frequency hail regions: the Great Plains and the Gulf Coast, unlike the single maximum from hail reports.
• The environmentally filtered MESH climatology showed better agreement with hail report characteristics (frequency, location, timing).
• Diagnosed hail days increased, and the spatial maximum in the Great Plains broadened westward compared to hail reports.

Conclusions:

• Improved MESH calculations combined with environmental filtering provide a more accurate severe hailfall climatology.
• This method corrects for biases in hail reports and reveals a more comprehensive spatial and temporal distribution of severe hail.
• The findings highlight the importance of advanced radar data and reanalysis for understanding severe weather phenomena.