Wednesday Observations 6/4: The Day with No Radar

 Today in the testbed all three forecaster groups were told to act as if they did not have any radar at their disposal, with offices in Albuquerque, Midland, and St. Louis.

Starting the day in Albuquerque CWA...The forecasters were quick to use OCTANE and GREMLIN to identify the strongest storms, and they picked out a storm just west of the city of Albuquerque. Increasing reflectivity values from GREMLIN, along with divergence signals from OCTANE Speed and the Cloud-Top Divergence products. Animation of GREMLIN and OCTANE (with radar included) are included below. The forecasters also leveraged the 12Z sounding from ABQ with its freezing levels, mid level lapse rates, and the wind profile.

GREMLIN 4 panel with the MESO scene (upper left), CONUS (lower right), MRMS composite reflectivity (upper right), and ABI MESO Clean-IR (lower left).

OCTANE with Speed (upper left), and the cloud top cooling and divergence flavors.

12Z Sounding from ABQ.

As the forecasters debated on issuing a warning, the 'real' NWS Albuquerque office issued a severe thunderstorm warning for 60 mph winds and 1 inch hail.

After some additional discussion, the HWT 'fake' Albuquerque office issued their own severe thunderstorm warning, also for 60 mph winds and 1 inch hail. They used LightningCast probabilities and ENTLN/NLDN flash locations to identify the thunderstorm 'core'.

Shifting to the Midland CWA...The forecasters in this office were watching for initiating convection just across the US-Mexico border in the higher elevations west of the Big-Bend region. There was discussion of the environment and how supportive it was for deep convection, especially related to the moisture/instability return from the Gulf during the forecast period.

OCTANE speed, cloud top divergence, and cloud top cooling products all showed the first robust updraft tapping into this instability with increasing speeds and strong cloud top cooling signatures followed by cloud top divergence.

The GREMLIN product from the MESO scene also reflected this cooling signature and strong gradients with increasing simulated reflectivity values. These values continued to increase until the HWT MAF office issued a severe thunderstorm warning. With 5-10 minutes of the warning, GREMLIN exceeded 60 dBZ. Another storm to the southeast also initiated and quickly intensified, with GREMLIN values also exceeding 60 dBZ.

We talked about the skill of GREMLIN to identify discrete convection and how realistic the values compared to our expectations from this machine-learning, satellite-based perspective. The takeaway from the forecasters was that GREMLIN has an easier time showing greater reflectivity values in discrete convective cores than multi-cell convection. 

I also looked at the ALPW product, and noted that the surface to 850mb layer showed the returning moisture, though I wonder if forecasters would like to see more frequent updates than hourly. I didn't have the chance to ask about this due to the active discussions during operations, but this seems like it would be the 'ideal' case since there was little cloud cover so sampling the lowest layers would be easier for the polar-orbiting sounders. How much this can help NWS forecasters searching for observations in remote areas is to be determined, but the product seemed to fit the conceptual model for the case.

-Dr. Thunder

Assessing GREMLIN skills

 Around 2000Z, a squall line was observed over Oklahoma and Kansas. GREMLIN successfully reproduces the overall reflectivity distribution seen by the KVNX radar, though it slightly underestimates the reflectivity of the convective cores (Fig. 1).

Fig 1: GREMLIN synthetic radar reflectivity (left) and KVNX NEXRAD actual radar reflectivity (right)

By 2016Z, convection intensifies, with convective cores covering larger areas. GREMLIN reproduces most of these features (Fig. 2), though some are heavily underestimated (black marks). The isolated convection—likely poorly resolved by satellite observations—appears to be particularly challenging for GREMLIN to accurately simulate.

Fig 2: GREMLIN synthetic radar reflectivity (left) and KVNX NEXRAD actual radar reflectivity (right). Black marks represent areas where GREMLIN did not reproduce correctly the intensity of the radar reflectivity field.

- Iceman

OCTANE Speed, Cloud Top Cooling, and Divergence Products in Central Oklahoma Storms, 3 June 2025

 With both discrete and cluster/multicell/linear storm modes, the cloud top cooling, speed, and divergence products proved fruitful in identifying convective intensity trends.

(Sorry, the gif got messed up a little bit)

Top right: OCTANE Speed        

Others: OCTANE Cloud Top Cooling (stoplight) and OCTANE Divergence (blues/purples)

The speed product showed not only the motion of the storm tops and the acceleration tendencies of the storm top features, but also highlighted (through the texture and color curves) the presence of other storm scale features like the overshooting tops and above anvil cirrus plumes. The color curve had been modified for this product to be the “compressed” color curve, which made gradients stand out. Additionally, this provided information about the environment the storms were tapping into, in this case showing that storms had ample shear to tap into and use to persist.

The divergence and cloud top cooling products were beneficial at different stages of life. The cloud top cooling products were a bit more useful in the initiation stage of storms, showing strong intensification of new updrafts, but became less useful as the updrafts became better established because the cooling was not the same magnitude you would expect from the initiation stage and it stood out less.

The divergence product felt useful in both of these stages of life, but especially once the storm had matured, since the relative strength of signals were about the same during both (i.e. same pink/red hues). While the re-intensification of the updrafts that cycled was signaled by the re-appearance of the green colors, the persistent signals of strong divergence gave better insight into the intensity trends over the storm’s lifespan compared to the cooling product, which was more instantaneous in nature. Once storms reached the mature phase, the channel 13 IR imagery became a better way of assessing storm top temperatures (not shown).

On the DSS front, the Cloud Top Cooling was more beneficial when used in tandem with LightningCast (not shown) during the initiation stage to assess the storm/updraft motions and decide whether DSS calls needed to be made. The early indication of convective cloud top cooling was a signal to forecasters that the clouds would likely become strong enough in the near future and would begin posing a lightning threat to Rudy’s event.

- prob30

Operational Feedback of Gremlin, Octane, and LightningCast during a Severe Weather Outbreak in Central Oklahoma

 I tested the OCTANE, GREMLIN, and LightningCast products during an actual severe weather event on 6/3/2025. My role during this testbed was that of the mesoanalyst.

Initial environmental analysis shows weak to moderate shear, which was determined via ARARS soundings and SPC Mesoanalysis, along with OCTANE imagery showing divergent / accelerating speeds within the storm anvils. VAD hodographs were used as convection developed to see rapid changes within the shear profile during the course of the event (as convection altered the broader environment). Shear increased as the event progressed. OCTANE and LightningCast were both useful showing the uptick in storm intensity as shear increased.

LightningCast was very useful picking out developing updrafts and embedded updrafts within broader areas of convection. We used this product to gauge which updrafts had the greatest potential to become severe in the near term. A strong uptick in lightning would indicate a rapidly strengthening updraft which would warrant further interrogation.

Similar to LightningCast, OCTANE was useful in determining which updrafts were trending towards severe. While in the mesoanalyst role, I would check to see which updrafts looked most intense (warmer colors paired with a very bubbly/convective appearance) and showed strong divergence. Radar analysis would then help us determine which individual cells to warn on, especially if the area of convection is multicellular and warning the entire thing isn’t ideal.

I didn’t use GREMLIN as much, since this area had good radar coverage. However, I did use it to keep tabs on its performance. The product seems to do well with picking out the strongest discrete/semi-discrete cells and potentially struggles with smaller/shallower storms and mergers.

Using these products, and working as a team with good communication, we were able to successfully warn a tornado in the Norman area along with various severe wind and hail.

- WxAnt

Nowcasting Convection with OCTANE

 SYNOPSIS - Scattered to numerous thunderstorms developed along a frontal boundary as it moved south into KS/OK/TX. These thunderstorms developed in a strong instability (3000+ j/kg MLCAPE) and modest shear (20-30kt effective, ~100 m2/s2 0-1km SRH) environment.

OPERATIONAL NOTES AND FEEDBACK - Using OCTANE to nowcast convective intensity and improve mesoanalysis situational awareness

Today’s event seemed to highlight a significant advantage of using OCTANE products to keep situationally aware during scenarios where there is a lot of convection. Oftentimes, radar can get incredibly messy when numerous thunderstorms are present, making it challenging to know which thunderstorms to focus messaging and warnings on. OCTANE products made this less challenging, by highlighting the thunderstorms with the strongest updrafts and/or most persistent updrafts. This combined with GLM lightning density provided valuable information for warning forecasters to decide which thunderstorms were the best candidates for warnings, and which ones to hold off on. Situational awareness (SA) can be quickly lost in events like these, and it is crucial to have a way to keep good SA. OCTANE provided an important tool in this endeavor.

The image below is one such example, showing two separate areas of convection over the WFO Norman (OUN) CWA (outlined in orange). In west-central OK, the OCTANE Cloud top Cooling/Divergence product shows notable updrafts with a persistent signal for notable storm top divergence, suggesting an increased risk for severe thunderstorms. Meanwhile, the thunderstorm activity to the east, in central OK, seemed to have more of a transient signal for strong cloud top divergence, with a somewhat less persistent signal. This suggested that the central OK convection would favor more of a pulse-type of severe weather setup, which informed future warning decisions (in my experience, pulse environments are often handled differently than environments that support long-lived / long-swaths of severe weather).

Additionally, the cumulus fields with green shading in the image above gave forecasters a heads up for which areas were seeing the most vertical development (ie. towering cumulus), which also was a tip-off for which areas may see new convective initiation.

While not shown, there was also a notable updraft that developed on a severe-warned thunderstorm west of Norman, OK. The OCTANE products nicely depicted this updraft as being more prominent than surrounding updrafts, and this particular thunderstorm went on to produce a tornado a short time later. This thunderstorm was embedded within a larger line of thunderstorms, which sometimes makes it less prominent when compared to radar interpretation, alone.

Probably the biggest takeaway here is that this one image provides a very quick overview of where convection may initiate, where convection is the strongest, what mode the convection is taking on, and where the biggest target of opportunity is for warnings and IDSS.

It’s recommended that satellite interpretation continue to be an important part of the mesoanalysis role of NWS operations, and OCTANE products appear to more quickly mesh what forecasters often look for in visible and IR products separately. This more efficient overview could save the mesoanalyst valuable time in assessing thunderstorm trends, providing quicker insight to warning and DSS forecasters.

- NW Flow

ICT Convection with Octane and LightningCast

 LightningCast

The LightningCast contours didn’t provide much insight due to high probability (>90%) of lightning pretty much the entire event. However we were able to utilize the dashboard for a DSS event. In Figure 1 below, the first thing I noticed was that the first lightning flash was recognized at approximately 2:57PM CDT where both v1 and v2 showed 90-100% probabilities. Looking back within the past hour at around 2:05 PM (not shown in the image), probabilities of lightning occurring within the next hour were approximately in the 50-60% range. It makes sense that the probabilities would increase with shorter lead times, however if this were being utilized for a DSS event and a partner was briefed at 2:05pm, they might decide to take a risk and hold off on sheltering since the probability is only 55% (therefore giving them a 50/50 chance in their eyes). Whereas around 2:20 PM when the probabilities started increasing to 80+%, there was only about a 30 minute lead time at that point. So the DSS events that require additional lead time due to further sheltering options or larger crowds may not be able to fully shelter by the time the first lightning flash occurs.

All that to say, I really like the utilization of this dashboard, however it would need to be used with additional tools (satellite, radar, etc.) in order to provide the most accurate information.

Figure 1: LightningCast Dashboard

Another item that was pointed out was that in Figure 2 below, you can see that the probabilities in v1 (red line) start to decrease around 4:10pm whereas v2 (green) remains above 95%. This could be due to the fact that maybe there were warming cloud tops, however with the ongoing lightning flashes in the vicinity, v2 would be the more reliable tool in my opinion

Figure 2: LightningCast Dashboard

Octane

The first cell that caught our attention was the cell in southwest Butler County. Figure 3 below shows the cloud top cooling and cloud top divergence (top right and bottom two panels), and you can see that cell shoot up with decent divergence aloft. We didn’t end up warning on it since radar looked pretty subsevere, however it was a good situational awareness tool to keep an eye on where the stronger storms were located.

Figure 3: Octane four panel

Later in the period, we did end up issuing two different warnings. The gif below (Figure 4) honestly doesn’t do it justice since I grabbed it a little too late, but there was a pretty pronounced divergence signature that started in Harper County near the city of Anthony that later pushed east into Sumner county. With the divergence remaining consistent and radar showing a pretty good wind signature, we ended up issuing a warning.

Figure 4: Octane four panel

I messed around with the colortables a little bit in Octane, switching to a stoplight color scale for the divergence and the magenta hue for the cooling. I’m still not fully sure which colorscale I prefer, so I’ll need to continue playing with both. However, comparing the three smoothing techniques for the divergence, I found myself looking at the highest smoothing (bottom right panel) more frequently since the lowest smoothing (top right panel) often looked too noisy. I think for situational awareness and assessing which storms to dive deeper into, the highest smoothing should work well.

- Fropa

Day 2- Using OCTANE In Warning Process

 Synopsis: A broken line of thunderstorms formed along a warm front from southern Oklahoma to east-central Kansas Tuesday afternoon. Storms entered a very moist environment with moderate to high MLCAPE and marginal shear. Due to a southwest to northeast storm motion, the largest threat was flash flooding, if storms became strong, damaging winds and large hail were possible.

Most of the activity in the ICT CWA was sub-severe (with the exception of flash flooding,) however there were times when a few storms pulsed-up enough to potentially produce damaging winds and/or large hail. One storm in particular had a lightning jump (GLM and ENTLN) at 2019Z over Greenwood county. This storm was entering an area that was untapped, however isolation was low.

Image 1 Caption: Snapshot of MRMS Reflectivity at -10C, GLM Flash Density, LightningCast ABI+MRMS, 5 Minute CG Flash NLDN and ENTLN 1 Minute Update Lightning

Using the OCTANE Speed and Direction Sandwich product it was evident that the storm of concern in Greenwood county showed changes in local shear coinciding with the lightning jump. The combination of this product with radar and lightning trends increased my confidence to issue a severe thunderstorm warning for damaging winds for 60 minutes.

Image 2 Caption: GOES-19 EMESO-1 and EMESO-2 CH-02 and Octane Speed products

- Eagle

ProbLightning Ending Time

 For Day 2, we were the Wichita Office. Our IDSS event had a high probability of lightning. Our group had a discussion about the idea of “lighting ending”, as that is a common question from outdoor events. In this case, ProbLighting did a great job of forecasting the ending time of lightning by using the time of arrival tool on the back gradient of the convection. Of course this would not work for back building storms or new development, but it performed well in this case. We incorporated that time info into our messaging.

The image above shows the ProbLighting (V2, left, V1 right) with ENL pulses on the left. This time of arrival tracker is shown in white on the left. Unfortunately AWIPS locked up toward the end, but this time of arrival gave a fairly accurate forecast that was used in the graphic.

The image above shows the graphic that we created at 346pm that showed the storms ending at 6pm using the time of arrival tracker on the back side of the Prob Lightning gradient. This turned out to be fairly accurate. In a real scenario, we could have probably briefed this information out to the decision maker.

- Updraft

KC Warning OCTANE

 For Day 2, we were the Wichita Office. They had mainly multi-cell convection, so we only issued 2 warnings, and these were for wind based on the 0.5 deg radar scan. In addition, our IDSS event was in lightning pretty much the entire time, so it was a fairly easy forecast to warn them, and then move on.

However, while evaluating the OCTANE, there was one event in WFO Pleasant Hill that showed persistent divergence aloft, and had this storm have been in our CWA, I would have issued a warning.

The animated gif above shows OCTANE speed (top left), Cloud top cooling (top right), Cloud Top Divergence (bottom left), and Cloud Top Divergence High Smooth (bottom right). In this case, notice the persistent high divergence values (red) in the lower two panels. 

The image above shows a zoomed-in look at the storm of interest. I would have issued a severe TS warning had this been in our area.

PUB LightningCast and GREMLIN Nowcasting

LightningCast

For this first day, I started out looking at Lightning Cast to gain familiarity with version 2 and see how it compares to version 1. The first thing I noticed was in southwest Pueblo County, where there seemed to be fairly frequent lightning. Version 1 in the top left panel (Figure 1 below) actually decreased in probability from 70% to 50%, whereas Version 2 in the top right panel remained at 70%. With both GLM and ENTLN depicting ongoing lightning, I think both versions should be showing higher probabilities. I’m wondering if it’s because both versions are so focused on the convection moving into southeast Pueblo County that they’re less focused on the stratiform lightning/less mature convection?

Figure 1: Four panel comparing LightningCast v1 (left panels) and LightningCast v2 (right panels)

Additionally, I tested out using the LightningCast dashboard for Fowler, CO beginning at 3PM MDT. One interesting thing to note was that it seemed to match better with the version 2 LightningCast in AWIPS versus with version 1, however both versions weren’t too far off. In the Figure 2 below, the left panel (version 1) shows between 30-50% probability of lightning, whereas the right panel (version 2) shows Fowler (purple dot in the image)  right on the border of the 70% probability. Comparing that to the dashboard (Figure 3) for the same time, the yellow line (version 1) depicts a 54% probability, with the green line (version 2) showing an 84% probability for 21:18Z. With MRMS reflectivity at the -10C level showing a cell up to 42 dBz just southeast of Fowler, I would tend to lean towards utilizing version 2.

Figure 2: LightningCast v1 (left panel) and LightningCast v2 (right panel)

Figure 3: LightningCast Dashboard

One final note on the LightningCast Dashboard - I thought it was interesting to see that version 1 in Figure 4 below, the yellow line (version 1) shows two separate upticks in lightning probability versus the green line (version 2) showing a steady decline in probability.

Figure 4: LightningCast Dashboard

GREMLIN

I was also able to look at GREMLIN, which was my first time assessing this product. Figure 5 below shows a four-panel, with GREMLIN (top left), MRMS Reflectivity (top right), Satellite IR sandwich (bottom left), and GLM Flash Extent Density (bottom right). Just looking at MRMS and IR, the first cell that draws my attention is the cell in southeast Pueblo County as it has higher reflectivities and cooler cloud tops. The cell in southern Otero county looks like the cloud tops are slightly warming with time. However once we start looking at GREMLIN, those two cells look to go back and forth in reflectivity, leading to less confidence in overall intensity. If I were located in an area with poor radar coverage, or if a radar was down and I had to rely on GREMLIN, it may not be straightforward as to which cell could eventually warrant a warning.

Figure 5: Four Panel comparing GREMLIN (top left), MRMS Reflectivity (top right), Satellite IR Sandwich (bottom left), and GLM (bottom right).

That being said, Figure 6 below shows a screenshot of the same four-panel at 21:41Z, which shows GREMLIN having a pretty good grasp on the convection in Stanton and Morton counties (just outside of the PUB CWA). So in this instance, confidence in the GREMLIN product would at least be higher than the previous example shown.

Figure 6: Four Panel comparing GREMLIN (top left), MRMS Reflectivity (top right), Satellite IR Sandwich (bottom left), and GLM (bottom right).

Final Thoughts for Day 1

Overall I enjoyed testing out both of these products. I definitely want to get more hands-on experience with GREMLIN as well as the LightningCast dashboard in order to see these in different scenarios/environments.

- Fropa