ProbSevere v3 in west Texas

Severe convection was rather marginal and sparse on 3 May, 2023. However, a few storms of note demonstrated better predictions for ProbSevere v3 (PSv3) over ProbSevere v2 (PSv2). 

A storm in the Texas Panhandle, southwest of Dumas, TX, was in an environment with moderate MLCAPE (1200 J/kg) and low-to-moderate effective bulk shear (30 kt). This storm was around for over an hour before it finally produced severe hail reports (up to 1.5" in diameter). Approximately an hour prior, however, PSv3 was much greater than PSv2; 62% vs. 4% (see Figure 1). In this case, PSv2 was too reliant on the ENI flash rate, which was only 4 fl/min. While lightning is important in PSv3 models, it is less affected by storms with a dearth of lightning than version 2, especially when other parameters show increased severe potential (in this case, MESH and mid-level azshear). 

Figure 1: ProbSevere contours, MRMS MergedRef, and NWS severe thunderstorm warning for a storm near Dumas, TX.

Figure 2: Time series of PSv3 and PSv2 probabilities for the storm near Dumas, TX, which produced 1.5" hail. 

The 00Z sounding from Amarillo, TX (Figure 3) might be able to shed some light on why the MESH was so high (up to 1.6") yet lightning was quite low (~6 fl/min) from both ENI and GLM sensors. In this case, the precipitable water in the column was quite low (about 0.68"). This, combined with the low environmental RH in the mixed phase region of the troposphere probably combined to produce relatively few collisions of liquid and frozen water particles needed to produce charge separation necessary for lightning production. Ice nuclei, on the other hand, seemed to accrete supercooled droplets efficiently, producing large hail stones.

Figure 2: Observed sounding from Amarillo, TX at 00Z on 4 May 2023.

Another storm in southwest Texas, near Pecos, also produced severe hail (1" diameter).  The lightning was also low for this storm, though PSv3 had 51% while PSv2 has 37%. The MRMS azimuthal shear parameters were zero here. This was likely because the average beam height of the lowest tilt of the closest radar was 10-11 km above ground level! The MRMS products compute azimuthal shear between 0-2 km and 3-6 km AGL. The missing azimuthal shear values for this storm reduced the probabilities of severe, but not quite as much in PSv3 as in PSv2. 

Figure 3: ProbSevere contours, MRMS MergedRef, and NWS severe thunderstorm warning for a storm near Pecos, TX.

East Coast Tornadoes

The past few days have seen several strong tornadoes along the U.S. east coast. A shortwave trough with ample upper-level diffluence provided a forcing mechanism for severe storms from Florida to Virginia.

Near Juno Beach, FL, a tornado damaged power lines, homes, buildings, and cars. Maximum wind speeds were estimated at 130 mph (rated EF2). Oddly enough, this tornado was only about 20 miles north of a weaker tornado from the day before.

Figure 1: ProbSevere v3 contours, MRMS MergedReflectivity, and NWS severe weather warnings for a storm near Juno Beach, FL. Outer contours on ProbSevere objects are colored by the probability of tornado.

ProbTor v3 (PTv3) is better calibrated than its v2 counterpart. There was a distinct ramp up in the tornado probability for this storm prior to tornadogenesis, compared to PTv2 (Figure 2). Part of this ramp up was due to higher 0-1 km storm-relative helicity depicted in the HRRR (~160 J/kg), which was much higher than the RAP. Storm rotation was also slowly increasing. Interestingly, this occurred at the same time that lightning and reflectivity-based parameters were decreasing. Despite low overall probability for tornado (20-30%), the ramp up, coupled with the fact that PTv3 remains on the low end overall (max of ~60%) could perhaps have tipped off users to look more closely at this developing storm.

Figure 2: Time series of PTv3 and PTv2 for a tornadic storm on the Florida coast, along with severe reports and NWS severe weather warnings.

The next day, Virginia Beach, VA was hit with an EF3 tornado, with peak winds estimated between 140 and 150 mph. Remarkably, no injuries were reported despite damage to 100 homes. In this case, PTv3 exceeded PTv2, and even hit 60%, which is a very high value for v3. The dip in probability shortly before the tornado was likely due to a pronounced reduction in mid-level azimuthal shear, which quickly rebounded (the 1-3 km mean wind also dropped from 37 kt to 30 kt during that time). 

Figure 3: ProbSevere v3 contours, MRMS MergedReflectivity, and NWS severe weather warnings for a tornadic storm near Virigina Beach, VA. Outer contours on ProbSevere objects are colored by the probability of tornado.

Figure 4: Time series for ProbSevere v3 probabilities, along with reports and NWS severe weather warnings.

Eastern Oregon storm

An elongated trough drew in enough elevated CAPE for a few storms to pop up in eastern Oregon. Very strong lapse rates (≥ 8-9.5 C/km) mixed down strong momentum from roughly 4-5 km AGL, producing downed trees and measured gusts to 65 mph. ProbSevere v3 (PSv3) showed rapid increases in the probability of severe at around 00:20 UTC and 00:50 UTC (Figures 1 and 2). 

Figure 1: ProbSevere v3, MRMS MergedReflectivity, and NWS severe weather warnings for a storm in eastern Oregon.

Figure 2: Time series of PSv3 probabilities for the eastern Oregon storm

The increasing MESH (up to around 1"), composite reflectivity (up to 63 dBZ), and ENI lightning (up to 10 fl/min) contributed to the first rapid rise in the probability of severe. A very strong satellite growth rate at 00:46 led to the next jump, up from 49% to 67%. One can see the cooling cloud tops in the GOES-18 visible/IR sandwich imagery that preceded 3 of the 4 severe wind reports (the first wind report was recorded at 00:41 UTC). 

Figure 3: GOES-18 10.3-µm brightness temperature and 0.64-µm reflectance for the storm in eastern Oregon.

In this example, the probability of severe hail seemed to be the strongest value; however, wind was the only hazard reported. While PSv3 generally has improved discernment among severe weather hazards, this would be a good case to look into to see if we can better incorporate model predictors in PWv3 that take into account the mixing of momentum very high in the atmosphere down to the surface, which is relatively common in the western U.S.