Investigating How Convective-Allowing Models performed during Severe Weather Events in the National Weather Service - Albany, New York Coverage Warning Area

Marissa McGuire, Brett Rathbun, Michael Main

Convective-allowing weather models (CAMs), including the High-Resolution Rapid Refresh (HRRR) and the North American Mesoscale Forecast System (NAM) are used to determine localized, convective patterns and evaluate various severe weather parameters to better establish forecasts. In this research, the predictive accuracy of the CAMs will be taken into account in comparison with the real-time archived radar imagery and severe weather indices and parameters from various severe weather events that occurred in 2022 and 2023.

To evaluate how the CAMs performed, the HRRR and NAM 12:00 UTC forecasts from the day of each given severe weather event were used and compared against the convection that actually occurred in the National Weather Service - Albany, New York coverage warning area. Severe weather parameters, such as 0 to 3 kilometer mixed-layer convective available potential energy (MLCAPE), 0 to 6 kilometer wind shear, and 500-hPa, 12-hour height falls (if applicable), were recorded in this research for each severe weather day. Each severe weather event for the 2022 and 2023 seasons were rated on a scale of -5 to 5 for each CAM model used, in this research, being the HRRR and the NAM models, and were rated concerning three categories: coverage, timing, and evolution.

Preliminary results will indicate the severe weather being evaluated using the Sherburn et. al severe weather criteria, by classifying the severe weather parameters (MLCAPE and wind shear). Additionally, each severe weather day will be classified as one of the four types of convective events: high CAPE, low shear; high CAPE, high shear; low CAPE, low shear; or low CAPE, high shear.