Modeling Maximum Hail Size in Alberta Thunderstorms

Abstract

A one-dimensional steady-state cloud model was combined with a time-dependent hail growth model to predict the maximum hailstone size on the ground. Model runs were based on 160 proximity soundings recorded within the Alberta Hail Project area for three summers between 1983 and 1985. The forecast hail sizes were verified against reports of maximum hail size gathered from a high-density observation network within the project area. The probability of detection (POD), the false-alarm ratio (FAR), and the Heidke skill score (HSS) were computed for the hail model forecasts and were compared with the skill scores for a nomogram method developed to forecast hail size in Alberta. The hail model was skillful in forecasting hail (POD = 0.85, FAR = 0.26, HSS = 0.64). On days with hail larger than 2 cm in diameter, the hail model performed slightly better (POD = 0.90, FAR = 0.40, HSS = 0.67). Analysis of the skill scores and hail-size forecasts suggests that employing a coupled cloud and hail model noticeably improves the overall skill and accuracy of hail forecasts as compared with those determined using the nomogram.