Forecasting outbreak type and severity using simulated fields of severe weather diagnostic variables

Recent studies have introduced the areal coverage technique as a means of diagnosing outbreak type and severity. This technique quantifies the spatial extent of severe weather diagnostic variables with magnitudes favorable for significant severe weather at a given time. Using reanalysis data, these studies have found that the areal coverage technique is statistically comparable to Storm Prediction Center (SPC) Day-1 convective outlooks in the discrimination of major severe weather outbreaks from less significant events. However, the technique has been untested using model-simulated output in a real-time setting.

This study examines the accuracy of WRF 1-day forecasts of areal coverage as a means of identifying major severe weather outbreaks. Simulations from 1 May to 15 June in the years 2011 through 2013, with setup identical to the real-time NSSL WRF 4-km horizontal grid, are evaluated using a dataset that identifies and ranks severe weather outbreaks that occurred during these periods. Preliminary findings indicate that simulated areal coverage exhibits considerable accuracy in the identification of the most significant severe weather outbreaks.