A cold front with ample moisture and instability ahead of it spawned numerous strong storms in the Southeast U.S. yesterday; particularly one long-lived supercell in South Carolina. A convolutional neural network model (CNN) was deployed in realtime on the 1-min GOES-16 mesoscale sector imagery. The model produces an “Intense Convection Probability” (ICP). The inputs for the model are the GOES-16 ABI 0.64 µm reflectance, 10.3 µm brightness temperature, and GLM flash extent density. It was trained to identify “intense” convection as humans do, associating features with intense convection such as strong overshooting tops, thermal couplets (“cold-U/V”), above anvil cirrus plumes (AACP), and strong cores of total lightning.

The animation below shows the ICP contours overlaid ABI 0.64 µm + 10.3 µm sandwich imagery, annotated with preliminary severe storm reports.

The long-lived supercell in South Carolina exhibited AACP and cold-U features, and produced numerous severe wind and hail reports (up to the size of tennis balls). While the NOAA/CIMSS ProbSevere models handled this storm well, the ICP ramped up on a couple of severe storms in northern Georgia before ProbSevere did. ICP for these cells exceeded 90% 15-18 min before ProbWind reached 50%. The ICP may be able to provide additional lead time and confidence to ProbSevere guidance for certain storms, utilizing spectral and electrical information from geostationary satellites. Incorporating ICP into ProbSevere is an active area of current research.

ProbSevere storm contours and MRMS MergedReflectivity for storms in GA and SC. The main or “inner” ProbSevere contour is shaded by the probability of any severe weather, while the outer contour is shaded by the probability of tornado, which appeared when that value was at least 3%, in this example.

An accumulation of ProbSevere storm centroids (white to pink squares, 50% –> 100%), NWS severe weather warnings, and SPC severe local storm reports from 12Z on May 5th to 12Z on May 6th [click to enlarge]