Today forecasters had an opportunity to look at LightningCast v1 (ABI only) and v2 (ABI + Ref10 inputs) in far southwest Texas, where radar coverage is quite poor.
LightningCast v2 for convection in southwest Texas. Background is GOES-19 C13, foreground blue pixels is GLM flash-extent density. Contour legend: green = 10%, yellow = 30%, orange = 50%.
LightningCast contours v1 for convection in southwest Texas. Background is GOES-19 C13, foreground blue pixels is GLM flash-extent density. Contour legend: green = 10%, yellow = 30%, orange = 50%, red = 70%.
For this area of developing convection, v1 was more bullish on two areas of convection that indeed became thunderstorms.
The signals in the day-cloud-phase-distinction RGB, which are represented as inputs in both versions of LightningCast, were indeed indicative of glaciated convection and high lightning potential.
GOES-19 day-cloud-phase-distinction RGB for southwest Texas (courtesy of College of Dupage NEXLAB).
This region was on the edge of the valid MRMS domain for the Reflectivity -10C predictor (see below).
Reflectivity at -10C. Gray is invalid regions, while the rest of the domain is considered “valid” to the LightningCast v2 model.
It’s possible that LightningCast v2 was expecting good MRMS Reflectivity -10C in that region, but that the co-evolution of Ref -10C with the ABI image predictors was slower than the expected co-evolution based on countless training examples in areas of better radar coverage.
The developers of LightningCast theorize that this could be ameliorated by using the Radar Quality Index (RQI) from MRMS, which quantifies the data quality. Supplying this as a predictor to LightningCast could help in regions with moderate to very poor radar coverage, and provide better uniform guidance throughout the CONUS.
MRMS Radar Quality Index in southwest Texas.
- Hail yeah
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