LightningCast in Texas

One team of forecasters was working in the San Antonio office yesterday. Convection began forming on a moisture boundary, captured by the GOES-18 mesoscale scan.

Under clear skies, LightningCast quickly picked up on the areas of glaciating cumulus clouds. Probabilities gradually increased along the moisture boundaries, emanating from the main storm, which went on to produce golfball-sized hail. LightningCast provided generally 35-40 minutes of lead time to initial flashes (from the 30% threshold).

Discussions with forecasters this week have included topics such as extending the lead time past 60 minutes, which is what LightningCast was trained for. Decisions by forecasters and event managers often have to be made 1-2 hours ahead of time, and the overall median lead time is about 20 minutes for LightningCast. LightningCast generally produces elevated probabilities once clouds begin to glaciate, as seen in the animation above. But what if we can make skillful predictions before the first signs glaciation, perhaps when an only-liquid-water cumulus field is present? That is one future research goal. Some ideas to accomplish this include exploring environmental fields (i.e., short-term NWP fields), as well as using time sequences of satellite data to better handle storm motion. We believe there is more information and value we can extract from the rich GOES-R observations, complemented with ancillary datasets.