Developing a Quantitative Measure of Convective Forcing to Evaluate High Resolution Rapid Refresh Ensemble (HRRRE) Variance
by Amber Liggett
Hazardous weather events have the greatest impact when they are not accurately forecasted. The quest for advanced lead times of accurate forecasts has motivated the need for understanding the correlation between convective forcing and ensemble skill/variance of the High Resolution Rapid Refresh Ensemble (HRRRE) model. To analyze this relationship, this study developed the Reflectivity Convective Forcing Categorization (RCFC), a quantitative method to categorize convective forcing using Multi-Radar Multi-Sensor composite reflectivity observations. Both reflectivity coverage and rate of change of reflectivity were examined during May and June 2016 utilizing RCFC. Several events exemplifying strong and weak forcing regimes were qualitatively analyzed using Storm Prediction Center mesoscale/surface analyses and upper air maps, for RCFC verification. Findings included strongly forced days having a greater reflectivity rate of change and coverage than weakly forced days. Results enabled future examination of the correlation between convective forcing and HRRRE ensemble variance/skill, facilitating HRRRE improvements.
About the Author
Amber Liggett is a junior Meteorology major and Mathematics minor from Beaver, PA. Her involvement on MU’s campus includes President of the MU American Meteorological Society (AMS) student chapter, Weather Watch talent member, MUTV News99 Weather personnel, and Campus Weather Service Lead Forecaster/Streaming Video personnel. She began this project as part of her summer internship research project with the National Center for Atmospheric Research (NCAR) program entitled Significant Opportunities in Atmospheric Research and Science (SOARS). Amber is passionate about improving lead times of severe weather due to its societal impacts of weather, so this project was a perfect way to begin that task. The project began as Amber qualitatively evaluated warm season case studies using Storm Prediction Center analyses, upper air maps, and surface maps. The forcing measure was then developed and stratified warm season events between May and June 2016 from strong to weak convective forcing. Then, several case studies were conducted to verify the quantitative measure of convective forcing. Finally, she examined how the measure will be used in future work to study HRRRE variance and skill under different forcing regimes. After completing her bachelor’s degree, Amber plans to attain a master’s degree in Emergency Management. Her career goals include becoming an expert AMS Certified Consultant Meteorologist, forensics meteorologist, meteorology liaison to emergency managers, and science writer focusing on severe weather. Therefore, the skills that she acquired while completing this project will definitely be used on subsequent endeavors.