What is already known:
What this study adds:
In this study, forecasters across the Southeast were surveyed to find out current practices/tools used when issuing forecasts and warnings during nocturnal (0300 UTC-1200 UTC), cool-season (November through May) tornado events. Additionally, forecasters were asked to rate personal beliefs regarding the possible forecasting utility added by novel statistical models as well as beliefs about potential personal use of such models both before and after viewing output from an existent statistical model. Readings from the well-calibrated, climatologically based Statistical Severe Convective Risk Assessment Model (SSCRAM) were shown to forecasters halfway through the survey to serve as the treatment for the sample. SSCRAM output was analyzed by Bunker (2017) to discover conditional probabilities of tornado occurrence – given certain environmental parameters in varying ranges – for this region during this specific kind of event. SSCRAM averages of conditional probabilities of tornado occurrence were found for six parameters in specific ranges; then, these averages were compared to forecasters’ subjective estimates of conditional probabilities, given the same parameters in the same ranges. Results of the study show a gap between forecasters’ knowledge and their calibration with the environment as well as a shift in personal beliefs regarding SSCRAM’s potential utility and use after being shown an example of that model’s output.