A simulated DSS event was placed in Garden City, KS, ahead of expected convection forced via cyclogenesis in eastern Colorado and a strong mid-level jet streak.
As severe storms began to approach the vicinity, LightningCast v2 (with Ref. -10C predictor) held probabilities in the 20-30% range, whereas LightningCast v1 (with ABI-only predictors) had probability of lightning in the 50-60% range for an hour, topping out at 75%. Forecasters could see the differences on the DSS lightning dashboard (Figure 1). No flashes were observed within 10 miles of the DSS location.
Figure 1: Lightning dashboard showing LCv1 (red) and LCv2 (green) time series of next-hour probabilities of lightning. No GLM flashes were observed during this time.
When we spatially compare LCv1 and LCv2 probabilities, we see that v1 contours extend much further northeast into the large anvil cloud towards Garden City, KS, whereas v2 probability contours are correctly more conservative.
This example demonstrates the benefit of data fusion: The ABI channels cannot “see” under that very thick ice, but the radar was showing no new convective development. Therefore, the LightningCast v2 model could reduce false alarm area for this DSS event, only needing to factor in anvil lightning potential and (to some extent) the motion of the storms.
Figure 2: Toggle of LCv1 and LCv2 probabilities. LCv1 probabilities extend further northeast towards Garden City, KS, creating more false alarm areas. Note well that these contours are NOT parallax corrected, but the probabilities in Figure 1 are. GOES-19 C02 reflectance and C13 brightness temperatures are plotted in the background, whereas GOES-19 GLM flash-extent density are the blue-to-yellow foreground pixels.
- Hail yeah
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