Northern Minnesota storms

At the 2021 HWT, one team of forecasters was working in eastern North Dakota and northern Minnesota yesterday. After monitoring a string of very weak-looking storms, a few storms finally tapped into some better deep-layer shear and overcame a capped environment.

One forecaster noted that a storm in Cass County looked severe, and while it was just outside of their county warning area, they would have warned it for 1" hail and 60-mph winds. The storm showed a small hail spike at 21:30 UTC (Figure 1). 

Figure 1: A small storm in Cass County, MN, with a hail spike. 

The team of forecasters also noted how PSv3 seemed to handle the marginally severe nature of this storm and others in the area better than PSv2, with PSv3 exhibiting higher probabilities earlier and maintaining them better than PSv2. 

Figure 2: ProbSevere contour with hover-readout and time series window, and MRMS MergedRef for the storm in Cass County. 

At 21:46, PWv3 was 49% whereas PWv2 was 11%. The MRMS VIL (30.3 kg/m^2), 0-3 km lapse rate (8.1 C/km), GOES intense convection probability (ICP; 24%), and 1-3 km mean wind were the top four contributors to the higher probability of wind for this storm

Further northwest, another storm showed a wind threat. PSv2 and PSv3 were fairly similar for this warned storm, which later produced a 61-mph wind gust near Red Lake. 15 minutes before the wind report, PSv3 achieved 67%, with the VIL, 0-3 km lapse rate, ICP, and 1-3 km mean wind contributing the most to the probability. 

Figure 3: ProbSevere contours, MRMS MergedRef, and official NWS severe weather warnings. 

Forecasters have remarked how they would use the time series feature in the ProbSevere AWIPS plug-in, if available at their offices. They also desire new enhancements, such as meteograms of more predictors and the ability to "dock" the window within a CAVE pane or tab. 

Nocturnal hailstorms in the Upper Midwest and ProbSevere v3

A cold front spawned numerous hail-producing storms in the Upper Midwest during the evening and overnight hours last night. ProbSevere version 3 (PSv3), which uses gradient-boosted decision trees with MRMS, ABI, GLM, Earth Networks, and NWP/SPC mesoanalysis data, was able to improve guidance over version 2 (PSv2) for a number of storms.

One of the more prolific hail-producing storms of the day formed west of Minneapolis, MN. PSv3 improved upon PSv2 with higher probabilities at a critical time before the first NWS warning was issued. 

Figure 1: ProbSevere contours, MRMS MergedRef, and NWS severe weather warnings for a storm west of Minneapolis, MN.

Figure 2: Time series of PSv3 and PSv2 for a select time period for the highlighted storm in Figure 1.

Looking at 01:50 UTC from the time series in Figure 2, we found that the top five predictors aiding to higher severe probabilities were:

1. ENI max total lightning density (0.28 flashes/min/km^2)
2. Eff. bulk shear (41 kt)
3. MRMS max 3-6 km azshear (0.008 /s)
4. MRMS max composite reflectivity (60.5 dBZ)
5. ABI+GLM intense convection probability (98%)

The intense convection probability (ICP) is an ABI + GLM based deep-learning model used to diagnose intense convection, and is a predictor in PSv3. 

Another storm to the northeast of the storm above also briefly produced severe hail. While the PSv3 probability was relatively low, it was still much higher than PSv2, which is an improvement that may be enough to bring a forecaster's attention to the storm.

Figure 3: ProbSevere contours, MRMS MergedRef, and NWS severe weather warnings for a storm WNW of Minneapolis, MN.

Figure 4: Time series of PSv3 and PSv2 for a select time period for the highlighted storm in Figure 2.

PSv3 peaked at 37% at 02:08 UTC, 6 minutes before the hail report. Performing a predictor importance analysis at this time, we found that the top five predictors aiding to higher severe probabilities were:

1. MRMS max composite reflectivity (65.5 dBZ)
2. Eff. bulk shear (47 kt)
3. MRMS max VIL (25 g/m^2)
4. MRMS max 3-6 azshear (0.007 /s)
5. MRMS max MESH (0.56 in)

A storm in northwestern Wisconsin fluctuated in probability, but eventually produced 1.25-inch hail.

At the time of the report (03:00 UTC), PSv3 was 47% and PSv3 was 13%. 

Figure 5: ProbSevere contours and MRMS MergedRef for a hail-producing storm in northwest Wisconsin.

At the time of the report, we found the top five predictors in PSv3 were:

1. MRMS max MESH (0.76 in)
2. MRMS max VIL (31 g/m^2)
3. Eff. bulk shear (52 kt)
4. MRMS max composite reflectivity (61.5 dBZ)
5. ENI total lightning density (0.21 flashes/min/km^2)

PSv3 should also help reduce false alarms around the country, relative to PSv2. This warned storm in northern Nebraska serves as an example. The maximum probability for PSv3 was 17%, compared to 49% for PSv2. There were no reports recorded for this storm.

Figure 6: ProbSevere contours, MRMS MergedRef, and NWS severe weather warnings for a storm in northern Nebraska.

One more example, just west of Duluth, MN, where PSv3 was about 20% higher than PSv2 at the time of a 1.25-inch hail report. At the time of the report, we found the top five predictors in PSv3 were:

1. MRMS max MESH (1.19 in)
2. MRMS max composite reflectivity (67.5 dBZ)
3. MRMS max VIL (26 g/m^2)
4. ENI total lightning density (0.23 flashes/min/km^2)
5. MRMS max 3-6 km azshear (0.007 /s)

Figure 7: ProbSevere contours and MRMS MergedRef for a storm west of Duluth, MN.

We hope these examples illustrate the improvement that forecasters will experience in using PSv3 at the Hazardous Weather Testbed. We also hope that they illustrate the benefit of intelligently fusing data together from the different observation systems we have available. We are actively working on ways to help users better interpret model predictions using analyses such as predictor importance ranking.