Comparing MRMS Data to Single Radar Data to Improve Severe Thunderstorm Warnings
Open Access
- Author:
- D'Iorio, Jennifer
- Area of Honors:
- Meteorology
- Degree:
- Bachelor of Science
- Document Type:
- Thesis
- Thesis Supervisors:
- Matthew Robert Kumjian, Thesis Supervisor
Johannes Verlinde, Thesis Honors Advisor - Keywords:
- meteorology
radar
MRMS
GR2Analyst
hail
severe
thunderstorm
warning
MESH
forecasting
National Weather Service
North Carolina
South Carolina - Abstract:
- Improvements to the forecasting of hail, especially severe hail (≥1inch in maximum dimension), can lead to advancements in the issuance of severe thunderstorm warnings. This improvement will not only aid National Weather Service (NWS) forecasters in severe storm verification and credibility, but will support their continued mission to protect life and property. The Multi-Radar/Multi-Sensor System (MRMS) developed at the National Severe Storms Laboratory (NSSL) has been used operationally by NWS forecasters since 2016. By rapidly integrating data from multiple platforms including radar, satellite, observational data, and numerical weather prediction models, MRMS can provide valuable and robust severe weather products to NWS forecasters. An independent sample of hail-producing thunderstorms that occurred across central North Carolina and central South Carolina from 2017, 2018, and 2019 was examined. A statistical analysis of MRMS products (NSSL Archive), including the Maximum Expected Size of Hail (MESH), was performed on the data. A statistical analysis was also completed on the GR2Analyst Hail Algorithm (Gibson Ridge Software) using Level-II single radar data retrieved from the National Centers for Environmental Information archive. A Contingency Table of Absolute Frequencies was made using the forecasted hail size from each product and the observed hail size for each event. The Probability of Detection (POD), Critical Success Index (CSI), False Alarm Rate (FAR), Hit Rate, and bias were calculated, and a comparison of these calculations from both products was performed. As hypothesized, it was determined that MESH from MRMS is more successful in accurately forecasting severe hail. The purpose of the analyses was to quantify the potential statistical correlations between the products and the occurrence of severe hail, determine product severe hail forecast skill, and any biases.