LightningCast for DSS at HWT

Several forecasters at the HWT were using the ProbSevere LightningCast meteograms to help inform communication and decision-making in simulated DSS events.

In Albuquerque, NM, we simulated their famed International Balloon Fiesta. Several areas of terrain-based convection were in the vicinity, when agitated cumulus clouds started heading toward the event from the southwest (Figure 1; red dot is the event location). Despite partial obscuration of the boundary layer clouds from upper-level outflow of another cell, LightningCast could still "see" the growing cumulus clouds and gradually increased the probability of lightning in the next 60 minutes, with a rapid rise in probability from 20:55 to 21:00 UTC (see Figure 2). The first flashes within 10 miles were at 21:23 UTC.

Figure 1: LightningCast probabilities of lightning in the next 60 minutes (contours), GOES-18 ABI daytime cloud phase distinction RGB (background), and GOES-18 GLM flash-extent density (foreground). Red dot is location of the Albuquerque International Balloon Fiesta. 

Figure 2: Top panel: LightningCast probability time series for GOES-18 5-minute (purple) and 1-minute (green) sectors; Bottom panel: Time series for ENI lightning (orange) and GOES-18 GLM flashes (blue).

Near Boise, ID, the DSS location was the American Aquarium Concert. A weakening upper low still supported sufficient deep-layer shear to produce strong storms heading for the concert from the east-southeast (Figure 3). As the storms edged closer, the probability of lightning continued to increase gradually, until a rather rapid increase from 21:45 to 22:15 UTC, from 20% to 80% (see Figure 4), as the anvil of the storm and some adjacent cumulus clouds moved right towards the event location (red dot in Figure 3).

Both GOES-East and GOES-West captured the increasing lightning potential at the simulated DSS event about 20-25 minutes prior to the first flash within 5 miles of the event. HWT forecasters at one point noted that the probabilities in AWIPS were not lining up exactly with the probabilities in the time series tool. We explained that in AWIPS, the contours are parallax-corrected, while the time series LightningCast data are not corrected. Based on their feedback (and that of other forecasters), we aim to provide parallax-corrected data in the time series capability very soon. 

We hope these cases illustrate the potential benefit of using an on-demand time series capability where lightning potential can be quickly ascertained, for both lightning initiation and advection scenarios.

Figure 3: LightningCast probabilities of lightning in the next 60 minutes (contours), GOES-18 ABI daytime cloud phase distinction RGB (background), and GOES-18 GLM flash-extent density (foreground). Red dot is location of the American Aquarium Concert in Boise, ID.

Figure 4: Meteograms of LightningCast probabilities (top panels) and lightning observations (bottom panels) for GOES-East (left) and GOES-West (right), centered at the American Aquarium Concert simulated DSS event.

The value of data fusion

We had an interesting storm develop in a radar gap in far eastern New Mexico yesterday. This is a great case study to demonstrate the value of data fusion in ProbSevere.

Figure 1 shows where the storm developed (the red circle), which was in a region of very poor "radar quality", as the eastern New Mexico KFDR radar was down. Thus, the closest radar was KAMA in Amarillo, TX.

Figure 1: Radar Quality Index for eastern New Mexico yesterday. The red circle is the approximate location of where the storm first developed. 

Figure 2: ProbSevere IntenseStormNet contours with GOES-16 ABI vis-IR sandwich product for a rapidly developing storm in eastern New Mexico.

One input into ProbSevere v3 is the probability of "intense" convection, as computed from IntenseStormNet. This is a deep-learning model that uses images of ABI 0.64-µm reflectance, 10.3-µm brightness temperature, and GLM flash-extent density to compute a probability of how "intense" the storm looks from a satellite perspective [paper]. 

The rapidly increasing IntenseStormNet probability, along with a favorable environment, and increasing total lightning flash rates helped jump the probability of severe despite poor radar reflectivity.

As the storm moved south and east into better radar coverage, radar reflectivity increased and the probabilities of severe further increased to above 70%. 

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

Forecasters at the HWT have noted numerous times how ProbSevere v3 has increased before v2, particularly noticeable in the regime we've experienced this week, where the storms have had a dearth of lightning at the developing stages. At the time in Figure 4, this storm had PSv3 of 36% vs PSv2 of 12%. 

Figure 4: ProbSevere and MRMS MergedReflectivity for a developing storm in a radar gap in eastern New Mexico.

Later on, this storm produced numerous large hail, severe wind, and several tornado reports. Interestingly, the ProbTor v3 was much higher than ProbTor v2 prior to the first tornado report. In Figure 5, we can see PTv3 is 47% while PTv2 is only 9%. Looking into this deeper, we found that the environmental information such as the 0-1 km storm-relative helicity (~ 30 m^2/s^2) and the 1-3 km mean wind (~15 kt) were very low. The HRRR values in PTv3 were much better (~100 m^2/s^2 for SRH and 27 kt for the low-level mean wind). I believe this is an indication that PTv2 was too dependent on environmental information, compared to PTv2. This also demonstrates that the HRRR had a better handle on the environment than the RAP. You can see the low 0-1 km storm-relative helicity in the SPC mesoanalysis (Figure 6).

Figure 5: ProbSevere contours (the outer contour is colored by the probability of tornado), MRMS MergedReflectivity, and NWS severe weather warnings.

Figure 6: 0-1 km SRH (contours) and storm motion (vectors) prior to tornadogenesis. The red circle shows where the approximate location of the storm prior to producing tornadoes. 

Figure 7 demonstrates how ProbTor v3 was much higher than ProbTor v2 early on. The vertical black lines in the top-left two panels represent the times of the first and last tornado reports. The interactive version of these time series have been saved off and are available here.  

Figure 7: Time series of ProbSevere probabilities and radar, satellite, lightning, and HRRR attributes for the tornadic storm in Figure 6. 

Two-inch hail on New Mexico/Texas border

Two-inch hail was reported on a storm on the New Mexico/Texas border, just on the edge of the Lubbock, TX CWA (Figure 1). At 21:04 UTC, 56 minutes prior to the report, ProbSevere v3 (PSv3) was 58% while PSv2 was 8% (Figure 2). At that point, the low ENI and GLM flash rates (≤ 4 fl/min) and modest environmental shear (≤ 30 kt) was dramatically reducing the PSv2 probabilities, whereas the shear was higher in PSv3 (36 kt) and the PSv3 models are less affected by low lightning (note: this storm eventually became well-electrified). The team in Lubbock today has noted how high PSv3 was prior to PSv2 early in the storms' development. While this is not always the case, it was true in Texas today because of the dearth of lightning early on.

Figure 1: ProbSevere v3 contours, MRMS MergedReflectivity, and NWS severe weather warnings for a storm on the NM/TX border.

 

Figure 2: Time series comparison of PSv2 and PSv3 for the storm in Figure 1. The annotation is valid for 21:04 UTC, when PSv2