ProbSevere v3 showing improvement

While the HWT forecasters didn't operate in North Dakota or South Carolina yesterday, I wanted to document several cases where Probsevere v3 (PSv3) was making improved predictions of severe weather, relative to ProbSevere v2 (PSv2).

In eastern North Dakota, very modest shear under a ridge helped these storms to get a little organization. Though PHv3 and PWv3 are rather low, the overall PSv3 probability was 44%, compared to PSv2 of 14%. Soon after the image in Figure 1, golf ball-sized hail was reported. In this storm, the low effective shear and lightning flash rate (12 fl/min) were hurting PSv2, while the MESH, ENI flash rate, low-level lapse rate (8.7 C/km), and decent mid-level azimuthal shear were the top contributors to the probability of severe. 

Figure 1: ProbSevere contours, MRMS MergedReflectivity, and NWS severe weather warnings.

A little further west and about an hour later, another storm showed a nearly 40% difference between PSv3 and PSv2 (50% vs. 13%). Despite a better flash rate and 1" of MESH, PSv2 was again hampered by low effective shear. Similar to the previous storm, the low-level lapse rate, MESH, and flash rate were helping PSv3. But in this storm, a strong satellite growth rate (not displayed in Figure 2) was the 5th leading positive predictor. Soon after the image below, there were two reports of semi-trucks blow over. Interestingly in this storm, the GLM flash rate was very low (1 fl/5 min) compared to the ENI flash rate (34 fl/min). This is another example showing how using data fusion helps create a more robust probabilistic model---when one data source is suspect (for whatever reason), others pick up the slack. We have also seen storms where GLM flash rates are much higher than ENI flash rates.

Figure 2: As Figure 1, but for a second North Dakota storm.

Several storms in South Carolina were showing some good improvement as well. A storm entering western South Carolina was pegged at 35% in PSv3, while only 3% in PSv2, owing to low MESH (0.47 in), low shear (~20 kt), and low/modest ENI flash rate (16 fl/min). In PSv3, a combination of good satellite growth (the growth rate was older, so not displayed in Figure 3 readout below, but still used in the model computations), modest reflectivity-based parameters, and a solid low-level lapse rate (9.1 C/km) combined to produce the 35% probability of severe. Reports of multiple trees down came in soon after this image.

Figure 3:  As Figure 1, but for a storm on the South Carolina /  Georgia border.

Further east, a similar story, with PSv3 13% greater than PSv2 (43% vs 30%). Dozens of trees and powerlines were down from this storm. The probability of wind was much higher than the probability of hail in v3.

Figure 4:  As Figure 1, but for a storm in central South Carolina

An analysis that was provided in the training slides for PSv3 showed that improvement was greatest in the moderate MLCAPE and modest/moderate effective shear regimes, which these storms fit into. One other point to note is that while ProbSevere v2 is often higher on very strong and mature storms, we've seen that quite frequently, ProbSevere v3 ramps up in probability sooner than v2, which we feel is a very important distinction and improvement. While not explicitly shown in the animation in Figure 5, v3 was again a little ahead of v2 in these storms in southwest Texas, where one team of HWT forecasters was working.

Figure 5: An animation of ProbSevere v3 contours, MRMS MergedReflectivity, and NWS severe weather warnings.

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.

LightningCast out west

One team of HWT forecasters is in Midland, TX, monitoring convection and serving DSS for the Midland Rockhounds Triple-A baseball team. As we got started, LightningCast for the GOES-17 mesoscale sector is already showing some initiation on the high terrain. However, an outflow boundary heading south-southwest is undercutting some convective cells. LightningCast has higher probabilities, but very few flashes so far behind the outflow boundary. We'll see how the outflow boundary interacts with the rest of the convection.

Figure 1: LightningCast contours and the day-land-cloud RGB from the GOES-17, and GLM flash-extent density from GOES-16.

Midland storms and ProbSevere v3

A slew of storms entered Midland's CWA. Both forecasters in Midland noted how ProbSevere v3 probabilities seem to better match their own subjective threat levels for hazards. This right-moving storm in Figure 1 has a probability of severe of 66%, compared to 34% in v2. It later dropped golfball-sized hail. 

One forecaster working this office said he likes how ProbSevere integrates and quantifies their own internal thought process to make objective and consistent guidance for warning decision-making.

Figure 1: ProbSevere contours, MRMS MergedRef, and NWS severe weather warnings for a storm entering Texas.

Forecasters working in Texas

Day 2 of the HWT has forecasters working in Midland, San Angelo, and Dallas/Fort Worth, Texas. The forecasters in DFW are also working a DSS event (PGA event in Fort Worth).

Storms are getting started along a dryline and other boundaries in south Texas (Figure 1). LightningCast picked up on these regions pretty well, with lead-times of 15, 25, and 60 minutes from the 50% threshold, for three different cells.  

Figure 1: LightningCast contours, GOES-16 day cloud convection RGB (1-minute meso scan), and GOES-16 GLM flash-extent density over south Texas.