What is already known:
What this study adds:
This study investigates when an RF algorithm’s day 1 severe hail probabilities differ from corresponding Storm Prediction Center (SPC) human-generated probabilities by at least one SPC outlook category. The goal of this study is to determine when an RF is most and least likely to add value to day 1 SPC human hail forecasts. RF forecasts are trained on forecast variables from the High-Resolution Ensemble Forecast System, version 2.1 (HREFv2.1) and observed SPC hail reports, using 627 days of data from May 2018 through April 2020. RF forecasts are compared against a continuous version of human-generated day 1 SPC hail forecasts, produced daily at 06z.
Analysis shows that the RF is especially skillful in reducing false alarm by forecasting one outlook category lower than that of the SPC. Additionally, when the RF forecasts at least one outlook category higher (lower) than the SPC, ensemble mean storm attribute variables including maximum 2-5 km updraft helicity, maximum upward vertical velocity, and maximum downward vertical velocity tend to have higher (lower) absolute values. Meanwhile, the distribution of these variables does not change much when the SPC forecasts at least one outlook category higher or lower than the RF. These findings suggest that RFs add value to the SPC by calibrating their probabilities based on the strength of simulated storms, while SPC forecasters add value to the RF by analyzing other (meteorological and non-meteorological) variables.