EWP Blog – Page 7 – Spring Experiments & Beyond

Day 1 GREMLIN and LightningCast

Posted in GREMLIN, LightningCast, SPG2025 on May 19, 2025 by Kevin Thiel.

Noticed that the meso GREMLIN was a little jumpy when it came to the apparent ‘strength’ of the storm. Tried to get a gif of it, but this isn’t the best…

Noticed that the CONUS did a better job of matching what the radar was showing (at this time frame). Same issues as above with the ‘jumpy-ness’. GREMLIN seemed to pick up more on the new convection (cell furthest to the south in image below).

When using ProbSevere with GREMLIN, can more easily see the slight shift in what it shows vs radar

LightningCast V2 appeared to consistently do a better job

– Lightning McQueen

4-Panel GREMLIN Satellite

Posted in GREMLIN, SPG2025 on May 19, 2025 by Kevin Thiel.

We discussed how we would handle warning this cluster of storms around 20:30Z Mon 19-May-2025, whether we would do one big SVR warning encompassing the whole cluster or concentrate into individual storms with different hail sizes and/or wind speeds. If I was warning this and saw a similar presentation in the radar for both clusters, I would begin with a larger SVR encompassing both storms.

The satellite product I use most often for cloud top cooling/warming for diagnosing convection growth is the Ch 13 IR. By using Ch 13 IR satellite and GLM Flash Extent Density, that helped me determine which updraft was the strongest and/or tallest. The overshooting top visible in the bottom left corner with the northern storm cluster suggests a quickly growing updraft that may start to produce large hail (and/or damaging winds) soon given the lapse rates and the explosive environment. Corroborating this with GLM FED and discussing with the group, we also came to the conclusion that the southern cluster of storms is probably broader but not as strong given its broader but less concentrated lightning presence, and might even be weakening below severe limits. With this information, I would have probably SVSed my warning to only include the rapidly growing northern cluster and maybe upping the hail size.

GREMLIN also tends to agree that they start off with relatively similar intensities, but eventually the northern storms take precedence. Using all four of these products together from the start to finish of the storms’ lifecycle would inform my warning decisions for initial issuance, SVSing, and eventual EXPing or reissuing downstream.

4 Panel loop below.

Loop of GREMLIN (top right), Composite Reflectivity (top right), Ch 13 IR (bottom left), GLM FED (bottom right)

– millibar

GREMLIN Comparison

Posted in GREMLIN, SPG2025 on May 19, 2025 by Kevin Thiel.

While it was noted in training materials that the GREMLIN based on 1-minute mesosector imagery would be a bit ‘noisier’, I wasn’t quite prepared for just how much that could show up. This is likely due to the use of the 1-minute lightning data, which will naturally be noisier than the 5-minute data for the CONUS-based GREMLIN. As you can see in the GIF below, this shows up especially strongly in the anvil regions of mature storms, where lightning in the anvil may be less frequent, and thus more noisy in the 1-min data, but the noisy data does show up somewhat elsewhere, too.

Comparison of GREMLIN based on GOES East Meso-1 (left) and GOES CONUS (right)

This would be a case where one would want to have the image looping to make it obvious what was going on, so you could know to ignore those simulated ‘returns’.

The mesosector GREMLIN also tends to have a bit ‘sharper’ resolution in most of its features, and also tends to have higher peak simulated reflectivity, again possibly/probably owing to the 1-min lightning data, which should be a bit less broadbrushed compared to the 5-min data used for the CONUS GREMLIN.

– Marko Ramius

LightningCast V1 vs V2

Posted in LightningCast, SPG2025 on May 19, 2025 by Kevin Thiel.

When initially getting into the Lightningcast product I noticed just some subtle differences between Lightningcast V1 (left window) vs V2 (right window) around the 1851Z timeframe to 1921Z. Near the Choctow and Pushmataha Counties had jumped up to 30% with even a small area of 50%, while the version 2 had a lower probability of lightning closer to 10-30% during that same timeframe. Will note on both, given the anvil cirrus from a strong storm off to the west may have been obscuring the area which looks like it lead to abnormally higher lightning probabilities than what otherwise would have occurred without the cirrus overhead. That being said, felt the Lightningcast V2 captured the threat better overall and kept the probabilities lower which would have lead me to not mentioning the area for thunderstorm probabilities just yet,

-Sting Jet

LightningCast Comparison

Posted in LightningCast, SPG2025 on May 19, 2025 by Kevin Thiel.

While the training touted cases where Version 2 (V2) of LightningCast had a clear lead time advantage over Version 1 (V1), many of the new cells I tracked today showed the opposite, with V1 showing higher probabilities sooner than V2.

It seemed like many of the cells were producing lightning very quickly after achieving even modest returns at the -10C level. In this case, the significant instability in the region today led to very rapid vertical cloud growth, which likely outpaced significant radar returns aloft. And while it is purely an educated guess on my part, that might have something to do with the weight given to the -10C reflectivity – if it needs a certain reflectivity threshold to really boost the probability, then the V2 product would be artificially slowing the increase in probabilities. Then in addition to waiting for the -10C reflectivities, you have to add in processing and dissemination lag time.

The V1 product, being based entirely on satellite data, was able to key in on just the rapid vertical growth and boost probabilities based on that alone, and not have to wait for the -10C returns to show up in MRMS.

Fig 1: Loop comparing LightningCast V1 (left) to LightningCast V2 (right)

Fig 2: Comparison of LightningCast V1 (left) and V2 (right) at 2041Z on 19 May 2025, showing V1 being first to have a 30% contour over the cell of interest in NW Arkansas.

Fig 3: Comparison of LightningCast V1 (left) and V2 (right) at 2046Z on 19 May 2025, showing both having a 50% at the same time, though V1 is larger in area.

Fig 4: Comparison of LightningCast V1 (left) and V2 (right) at 2051Z on 19 May 2025, showing V1 being first to have a 70% contour, while V2 still only has a small 50% area.

Fig 5: Comparison of LightningCast V1 (left) and V2 (right) at 2056Z on 19 May 2025, with the first GLM Flash Extent Density return (blue square) noted at 2059Z. Note that V1 had a 70% contour nearly coincident with the GLM Flash square, while V2’s highest return was still only 50%, and well displaced from where the lightning actually happened.

While I don’t doubt that the -10C reflectivity can help in many scenarios, on days like today it didn’t seem to help much, if at all, and in many cases the satellite-only V1 seemed to do a bit better. As I said, it’s my hypothesis that this is due to the rapid vertical development outstripping the production of -10C returns. Additionally, I would be curious if testing out MRMS Vertically Integrated Ice (VII) instead of -10C reflectivity would produce better results (if it hasn’t been tried already)

– Marko Ramius

OCTANE-GREMLIN Comparison for May 8th convection across eastern Tennessee

Posted in GREMLIN, OCTANE Speed Sandwich, SPG2025 on May 8, 2025 by Kevin Thiel.

MesoAnywhere was very useful during this event. While there was a meso sector across the Tennessee valley, MesoAnywhere did a great job providing useful details pertaining to warning operations. Growing cu was evident early in the event along with mesoscale boundaries. The product continued to provide value during the event as other channels were used to measure storm intensity trends.

GREMLIN struggled early in the event with a storm just north of the CWA over Whitley County, Kentucky. This storm quickly became severe warned as there was a large Three Body Scatter Spike (TBSS) and impressive tall intense reflectivity core with ZDR/CC/KDP drop out. GREMLIN caught on I believe after 5min or so, but reflectivity values were still lower and not as concerning as MRMS. It was also interesting to note the storm entering western portions of the forecast area looked more intense on GREMLIN at times. If there was no radar data, GREMLIN may have made me focus more on issuing a warning for the storm to the west of the CWA. However, OCTANE data clearly showed a stronger STD signal on the storm to the north which is what made me initially go look at the 88D radar data for it.

GREMLIN was a useful tool during the event as it did catch on to stronger cells that developed, but it was slightly slower than MRMS or 88D radar data at times and would smooth out more impressive signals in reflectivity that helped issue timely severe warnings for hail. If there is no radar data, GREMLIN is certainly still a useful tool. The more tools, the better!

Here is where OCTANE data clearly showed a stronger STD signal on the severe storm to the north compared to the one entering our CWA from the west. This gave me a heads up to go look at the 88D radar data to see if a warning was warranted. The smoother STD procedures make it slightly easier to see the signal.

OCTANE STD has been one of my favorite tools in the experiment. I found it very useful to quickly identify the strongest storms in my CWA that warranted my attention. It was also helpful for understanding storm intensity trends as it has cloud top cooling overlaid in the product. The low-med smoothing and high smoothing were easier to read than the sn smoothing STD procedure. The no smoothing was splotchy which made it more difficult for my eyes to quickly discern which storms required the most attention for potential convective warnings. The tool was amazing for all of the convective events through the week, but I could see this procedure not being as useful in certain convective modes where STD signals may be weaker. I would love to learn more about what thresholds to look for in the product! I’m sure that will be a great future research project, and I appreciate all of the hard work from the researchers involved with this experiment.

– Ricky Bobby

Odd LightningCast Dashboard Reading

Posted in LightningCast, SPG2025 on May 8, 2025 by Kevin Thiel.

An odd or false reading from LightningCast occurred on the Dashboard readout on May 8, 2025. The IDSS event was the Southern Skies Music Festival in Knoxville, TN. The screenshot below shows the Max Lightning Potential (10-mile radius) increasing dramatically after 14:40 UTC while the other LightningCast options don’t suggest any potential for lightning (in next 60 minutes) until after 15:45 UTC and even then, the others didn’t have any probability over 30%. On the plainview map comparing LightningCast 1 vs LightningCast 2 (Figures 1, 2, 3), the contours finally overlap the 10-mile event ring by 20:31 UTC and match up with the Dashboard probability at the same time (See Figure 2). Discussions within the HWT noted the issue could likely be a domain or pixel issue for the Max P.

Screenshot of the LightningCast Dashboard for Southern Skies Music Festival on May 8, 2025 from 19:40 UTC to 21:25 UTC. Interesting to note the blue arrows pointing to high probability of lightning depicted by the Max while the others remained less than 10% until 15:45 UTC.

Figure 1: At 19:46 UTC, the lightning potential approaches the 10-mile radius when the Max probability suggests nearly a 50% probability of lightning in the next 60 minutes.

Figure 2: At 20:31 UTC, the 10 and 25 probability of lightning enter the 10-mile radius.

Figure 3: At 21:26 UTC is when the probability of lightning really tapers off, even the Max P version.

Loop of the LightningCast version 1 and 2 surrounding the Southern Skies Music Festival.

– Podium

Severe thunderstorm warnings ONLY using satellite data

Posted in GREMLIN, LightningCast, OCTANE Speed Sandwich, SPG2025 on May 8, 2025 by Kevin Thiel.

May 8, 2025 was an interesting day for the experiment because “WFO GSP” was not allowed to utilize radar to issue severe thunderstorm warnings. I relied heavily on OCTANE Speed and CTD/cooling products and GREMLIN for making these decisions. At first, I struggled a bit with mentally shifting everything to the southeast due to parallax. After I began to utilize the ENTLN data as a proxy for storm core, it was better to estimate storm location and movement (although still not perfect). By the end of the day, I ended up issuing seven severe thunderstorm warnings. I found myself relying more on the CTD and cloud top cooling panel than the speed sandwich. Since it was my second day using the OCTANE products, I was quicker at picking up on signals in the CTD panel that suggest the presence of stronger thunderstorms. Having the CTD in one number compared to having to mentally calculate it while using the speed sandwich was helpful when working in simulated operations when a couple seconds does make a difference. I also found GREMLIN useful as a situational awareness tool to help distinguish which cells should potentially be interrogated more.

Here is a loop of OCTANE Speed Sandwich and the CTD and CTC products from two severe thunderstorm warnings I issued. The severe thunderstorm warnings were issued for the same storm, with the second one being issued as the first one was expiring. Looking at the OCTANE data combined with ENTLN (Image 1), it was clear that the storm was taking a turn to the right. I don’t know the specific values that CTD was showing, but I do believe this storm had values of 4+.

Image 1: Two severe thunderstorm warnings in OCTANE SS and CTD/CTC with Lightning Cast v1 and v2 overlaid. ~21:20Z to 21:56Z

GREMLIN (Image 2) also subtly shows this change in direction. What is interesting is that GREMLIN using ECONUS actually maxed out with a value of 60.4 dBZ.

Image 2: GREMLIN loop for the same two severe thunderstorm warnings in Image 1.

Image 3: Severe thunderstorm warning with OCTANE SS and CTD/CTC. ~21:56Z-22:22Z.

Image 4: Severe thunderstorm warning for the same time but with GREMLIN.

Another severe thunderstorm warning I issued, was showing CTD values of 4+ that prompted a warning. In GREMLIN, the strength of this cell was not as obvious in the ECONUS version, but slightly more prominent in EMESO-2. GREMLIN shows these cells basically merging, but I don’t know if that was reality. Looking at these loops compared to the movement of the lightning data, I don’t think my strom track was very good. In cases where radar is unavailable, I could see other novice warning forecasters also struggling with identifying storm track and motion when using strictly satellite data and also trying to mentally correct for parallax. This may not be an issue for more experienced warning operators though.

– Golden Retriever Lover

Greer Severe Weather Blog

Posted in GREMLIN, OCTANE Speed Sandwich, SPG2025 on May 8, 2025 by Kevin Thiel.

From 1940Z to 1950Z, there was a cell developing right over Madison county. If you look at the cloud top temperatures in the Octane 4 panel below, you will see that there is cooling spike. Gremlin also picked up on high reflectivities in the same area with actual ENI total lightning increasing in density. Gremlin also showed an increased lightning intensity signal. We issued a warning on that storm and ¾ inch hail was reported.

2149Z

Interesting feature with Gremlin that would possibly suggest that there is a hook on the storm noted below to the right. Hence we issued a SVR with TOR possible tag. Looking forward to seeing if there are any reports with this storm.

-Jolly Rogers

Web based LightningCast for a DSS event

Posted in DSS, LightningCast, SPG2025 on May 7, 2025 by Kevin Thiel.

My office’s internet went down hard for the entire day, so I had to utilize a mobile hot spot. AWIPS in the cloud was very sluggish and unusable on the mobile hotspot so I opted to only utilize the web based tools for today.

With a focus on the Brisket Appreciation Society Annual Bash in Beaumont, TX, storms started to emerge to the west and southwest of the event around 2 PM. I found the DSS dashboard useful when monitoring the specific location, but I wanted to use the LightningCast map as well for overall situational awareness. It was a little difficult for me to find exactly where the location was, so it would be useful for the map to have a dynamic layer for the DSS events.

I created a public graphic around the time lightning started near the to move closer to the DSS event. I generally utilized radar and LightningCast dashboard for the DSS event for the messaging. I did not include an image of the LightningCast for the graphic because it was already above 80% when I created the image. Because of this, there was very high confidence that lightning would occur, with the goal of the graphic to inform people of the approaching storms and the associated hazards.

LightningCast (both v1 and v2) stayed very high during the entirety of the event. When looking at the DSS dashboard, the probabilities within for the event increased to >80% 30 minutes before lightning was within a 10 mile radius of the event. There was an issue with the 1 minute data that caused that dip to 0. However, the 1 minute data is very noisy, and in this case, is not an improvement when compared to the 5 minute data.

– Golden Retriever Lover