ICP in an MCS

The Intense Convection Probability (ICP), the product of a convolutional neural network (CNN) trained with ABI 10.3 µm brightness temperature, 0.64 ABI µm reflectance, and GLM flash extent density, highlights intense parts of a MCS that began in Kansas and traveled through the mid-Mississippi Valley. Below, the product was contoured at the 25%, 50%, and 90% levels (blue, cyan, and magenta, respectively), and overlaid 10.3 µm and 0.64 µm sandwich imagery from ABI.

In the movie below, higher ICP is generally found with cold, "bubbly" cloud tops as the MCS propagates, and corresponds well to regions of numerous severe hail and wind reports. Part of the MCS decays in south central Tennessee and northern Alabama, producing many wind reports. The storms in this region had decreasing reflectivity, a dearth of total lightning flash rates, and warming 10.35 µm brightness temperatures, diminishing the ICP. This part of the MCS was becoming decoupled from its source of MUCAPE and forcing, resulting in outflow-dominant storms.

We are hopeful that the ICP will improve ProbSevere by leveraging important satellite information during the mature phase of a storm's lifecycle, as well as quickly identifying developing intense convection emerging from thick ice clouds (e.g., anvil clouds).