Fall severe weather outbreak over the Southern Plains

A strong, negatively tilted, diffluent short wave trough forced severe thunderstorms in the Southern Plains ahead of and along a potent cold front yesterday. Figure 1 shows a high-level evolution of the storms and ProbSevere v2 (PSv2) from discrete to more linear storm modes as the event proceeds.

Fig. 1: GOES-16 IR, MRMS MergedRef, ProbSevere storm contours, and NWS warnings.

One supercell that traveled through downtown Dallas, TX dropped a strong, EF3 tornado which produced much damage, which an NWS survey marked 01:58 UTC as the initial touchdown time. The storm went on to produce an EF1 tornado, starting at 02:36 UTC.


This storm was the right moving supercell after a left split (see Figure 2). Figure 3 shows the time series of PSv2 model output before the split, while Figure 4 shows the time series after the split, including NWS warnings and preliminary storm reports. The storm initially exhibited a strong satellite growth rate and a spike in MRMS MESH, which contributed to the rapid increase in ProbHail and ProbWind.

Fig. 2: ProbSevere, MRMS MergedRef, and NWS severe weather warnings in AWIPS2, depicting the storms affecting the DFW metro area.

You may find the time series of PSv2 model predictors for Figure 2 here and Figure 3 here. 

Fig. 3: Time series of ProbSevere models for a tornadic storm prior to it splitting. NWS warnings and preliminary storm reports are on the lower axis.

Fig. 4: Time series of ProbSevere models for a tornadic right-moving supercell after it split. NWS warnings and preliminary storm reports are on the lower axis (EDIT: tornado report times are the start times of tornadoes from an NWS survey).

An experimental convolutional neural network, which uses ABI channels 02 and 13, as well as flash extent density from the Geostationary Lightning Mapper, was deployed on this scene. The model produces an "Intense Convection Probability" (ICP). The 50% and 90% contours correspond well with robust satellite signatures, such as overshooting tops and enhanced-Vs. While there is also good correspondence with reports, probabilities of < 25% are present for some hail reports early in the event and some wind reports late in the event, showing that all severe weather is difficult to detect with a satellite-only approach. Regardless, such a model may be able to enhance ProbSevere, especially in regions with no radar coverage. See this CIMSS blog post for more information and examples from this model.