To examine the skill of 1-km horizontal grid spacing for next-day tornado prediction, we produced a large set (N=497) of 36-hour, CONUS-wide, CAM forecasts using 3-km and 1-km horizontal grid spacing and extracted a variety of low-level surrogate diagnostics. Forecasts of tornadoes were produced by applying a set of thresholds to the surrogate fields and smoothing the forecasts; forecasts were verified against SPC tornado reports. The 1-km grid spacing forecasts were more skillful than the 3-km grid spacing forecasts, producing larger fractions skill scores (differences > 0.1) and larger Brier skill scores over all smoothing length scales. Consistent with prior work, shallower integration depths closer to the surface were more skillful (i.e., 0 – 1 km AGL UH) than deeper integration depths (i.e., 0-3 km AGL or 2-5 km AGL UH). The most skillful next-day tornado forecasts were produced using 0 – 1 km AGL UH from the 1-km forecasts, although smoothing was still necessary to improve the reliability at the expense of sharpness. Reasons for the differences in skill between the 3-km and 1-km grid spacing forecasts will be discussed.
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