The Effectiveness of NSSL's Experimental Warn on Forecast System for Severe Weather and Flash Flooding Events in The Carolinas in 2020-2021

Faculty Sponsor

Kevin Goebbert


Arts and Sciences



Presentation Type

Poster Presentation

Symposium Date

Spring 4-28-2022


The Warn-on-Forecast system is an experimental system of computer models that is being developed to improve forecasts, warnings, and decision support for high impact thunderstorm events. It is designed to give accurate predictions of thunderstorm hazards, such as hail, wind, flash flooding, and tornadoes. The goal of this project was to look at the effectiveness of the Warn-on-Forecast system in predicting these hazards in the Carolinas, and to identify elements that could improve ease of use for weather forecasters. Storm reports were gathered for the days that the Carolinas were in the forecast area for the system during 2020-2021. These reports were compared to the different parameters in the system to see how well the Warn-on-Forecast system was able to predict identified hazards. Findings reveal the Warn-on-Forecast system did a reasonable job at predicting hail and flash flooding; however, it underestimated the potential for wind.

Biographical Information about Author(s)

Natalie Vernon is a senior in the Meteorology department. Natalie has always had an interest in weather and how to protect others by forecasting the weather hazards. A Hollings Scholarship recipient, Natalie worked with scientists at the Columbia, SC office of the National Weather Service to complete a project examining weather model effectiveness in predicting severe weather in the Carolinas. Natalie plans to continue her studies of operational meteorology as she attends graduate school.

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