Can we predict the predictability of high-impact weather events?

These information-rich diagnostic fields allow us to quantify the predictability characteristics of a specific forecast event. This work harnesses insights from a month-long dataset of ESA applied to convection-allowing model precipitation forecasts in the Central Plains of the United States.

Temporally averaged and spatially averaged sensitivity statistics are correlated with a variety of other metrics, such as skill, spread, and mean forecast precipitation accumulation. A high, but imperfect, correlation (0.81) between forecast precipitation and sensitivity is discovered. This quantity confirms the qualitatively known notion that while there is a connection between predictability and event magnitude, a high-end event does not necessarily entail a low-predictability (high-sensitivity) forecast.