Statistical Comparison of HRRR and RRFS Convection-Allowing Models During Severe Weather Risks of 2022-2023

Numerical weather prediction is the most robust tool available used to forecast future weather. Through time, the models that use numerical weather prediction have increased in accuracy to the point where 3-day forecasts are nearly 90% accurate. Despite the prowess of numerical weather models, they remain imperfect due to a multitude of reasons. The initial condition problem, poor physical understanding of the atmosphere, or generalized parameterization schemes cause model error leading to incorrect forecasts. This is especially the case when the atmospheric conditions fed into the model are particularly complicated. These high impact events can cause loss of property, or in rarer cases, loss of life. This study investigates case studies of high impact events and compares how well the HRRR and RRFS operational models forecasted them. Understanding and identifying consistent flaws in NWP models during similar atmospheric set-ups will allow for implementation of correction techniques that will allow for improved forecasts, resulting in a public more aware of extreme weather.