Thorough Probabilistic Verification of Storm Prediction Center Forecasts

Eight years of Day 1 and 4.5 years of Day 2-3 probabilistic convective outlooks from the Storm Prediction Center (SPC) are converted from the archive format of lists of points along a contour to interpolated probability fields on a consistent high-resolution contiguous United States (CONUS) grid. This extended record of SPC forecasts is then verified using traditional probabilistic forecast metrics, such as the Brier Skill Score and reliability diagrams. It is found that there is little trend in forecast skill over the period of record, and relatively little seasonal cycle in forecast skill as well. Highest skill is noted for severe winds, with lowest skill observed for tornadoes; for significant severe criteria, the opposite discrepancy is observed, with highest forecast skill for significant tornadoes and approximately no overall forecast skill for significant severe winds. For all elements, but especially for severe winds and hail, a substantial north-south skill gradient exists, with higher skill exhibited in forecasts over northern and eastern CONUS with lower skill in the south and west. This distribution was also seen in Day 2 and Day 3 forecasts, with skill decreasing with increasing forecast lead times. Forecasts were also verified in CAPE/shear parameter space; forecasts struggle most in very low shear environments, and secondarily in very high shear/very low CAPE environments. Severe wind and hail forecasts are found to have an overforecast bias, while Day 2 and 3 forecasts have an underforecast bias.