Lightning Cast: Real-Time Monitoring for DSS

The LightningCast Dashboard is an excellent tool to monitor and predict the probability of lightning at a point, which allows us to easily provide decision support services (DSS) for outdoor events.

Here’s an example from today for the Clown Rodeo on the south side of Lubbock, TX:

Notice the LightningCast probabilities for both the ABI and ABI + MRMS generally remained between 0 to 20% during the duration of the event.

These probabilities were associated with developing cumulus clouds in the area, which can be seen in the Day Cloud Phase Distinction RGB:

Typically, if a meteorologist sees developing cumulus similar to shown above in the Day Cloud Phase Distinction RGB, this would result in an increasing concern for lightning at that location. However, it is challenging to quantify this concern and message it probabilistically to our partners. LightningCast gave us confidence to message our partners there is a low probability (10 to 20%) of any lightning strikes within the next hour.

-Vrot

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Using LightningCast and MesoAnywhere for Alligator Wrestling

Since we are relatively limited with the products we can use today as the meso sector doesn’t fully extend down into JAX’s area, I will be mainly using LightningCast and MesoAnywhere today. We are able to use the CONUS sector for GREMLIN, though I’m not too sure how useful it will be today with good radar coverage via KJAX. However, there are some more storms moving in from TAE’s area and with KVAX out for the day, it could prove useful.

There is already some discrepancies with the event so far with LightningCast V2 being slightly more bullish with the threat at the Alligator Wrestling event this afternoon as shown below in Figure 1.

Figure 1: LightningCast V1 (left panel) compared to V2 (right panel).

The LightningCast dashboard also shows this discrepancy (Figure 2) with a notable spike in probabilities from V1 followed by a significant decrease and a pretty gradual increase for V2.

Figure 2: LightningCast dashboard comparing V1 (warmer colored lines) and V2 (green line) over time at the event.

Additionally, MesoAnywhere has proven useful since we do not have a meso sector today. I found that it has been pretty good identifying more dominant storms in decaying clusters with pretty good lead time compared to using 5min imagery. Pretty obvious that this would be useful, but I see it as a pretty great tool as a former Florida WFO meteorologist. A lot can happen in 5 minutes and I see this being quite useful for summertime pulse convection.

As of 4:10PM ET, Lightningcast V2 continues to remain more bullish than V1. Figure 3 shows the contours in AWIPS and Figure 4 shows the dashboard. Both versions appear to be on a steady incline, though V2 is noticeably higher.

Figure 3: AWIPS LightningCast with V1 on the left and V2 on the right. The 30% contour is noticeably further south toward the Gator Wrestling Match and also has higher probabilities off the coast of St. Johns county.

Figure 4: LightningCast dashboard showing the probabilities across each version. As of typing this, both have begun to even out.

However, it does appear that V1 did a better job at picking up on the lightning threat for a storm over in TAE’s area covering Berrien and Lanier counties in GA. In Figure 5 below, both versions had a 90% contour over the developing storm with lightning following not too long after.

Figure 5: LightningCast V1 and V2 indicating the threat of lightning for a storm over Lanier and Berrien counties in GA.

In Figure 6, LightningCast shows the threat decreasing accordingly with time as the storm begins to ingest some cooler air, likely outflow from the southern storms. This product appears to be quite good with initiation and I hope we get more cases like this over the next couple days.

Figure 6: The storm over Berrien/Lanier counties in GA showing less of a signal for lightning over the next 60 minutes as it weakens.

Regarding the Gator Wrestling, chances have decreased to zero over time. Both V1 and V2 remained on the lower end for probabilities and verified well with only one GLM strike within 10mi (Figure 7).

Figure 7: Not a whole lot going on at the Alligator Wrestling Match.

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Convective Decay Using LightningCast

We found LightningCast to be very useful for the decay of pulse-severe type convection. While the probs jumping up were great for CI, the opposite is true for cessation. The loop below demonstrates LightningCast signifying the cluster of cells decaying as they move across the JAX CWA, while remaining in a generally low-end GLM FED and a near constant ice phase. In other words, the LightningCast was a little quicker to jump on weakening trends than satellite data. This would also be very useful for DSS where we can brief a partner with an outdoor event with a quantitative probability that lightning will be over at their point within 60 minutes.

-millibar

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Day 3 – The Train Is On The Tracks OCTANE

I definitely felt more comfortable using OCTANE today and now that I understand it better, I was able to look at it compared to 10.3 imagery and I found that useful in differentiating which storms were still strengthening.

Jason showed us how to play around with the color tables for the OCTANE product and basically invert them so that the purples/pinks (cooler colors) represent cooler cloud tops, and the yellows/oranges/reds are the divergence. Conceptually I think this makes more sense to me putting cooler colors = cooling cloud tops.

GREMLIN

I feel like I saw very mixed results with GREMLIN with this event. There were times when the meso performed the best I’ve seen it all week (below)

…and then just two minutes later, not so much.

I’m not sure what attributed to the sudden drop off on what on radar appeared to be the strongest storm.

Later, GREMLIN seemed to be doing very well with the areas of more stratiform precip, which I don’t believe I’d gotten to see up until this point. Was curious if it typically does better in that type of environment.

LightningCast

I wish I had grabbed more of the LightningCast plots since it was probably the product I was looking at the most since I was doing the DSS messages, but the plot below was the only one I did grab.

I was curious about the sudden dip in the V2 product because I don’t think I’d seen it be lower than both V1 before.

– Lightning McQueen

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DSS messaging with the Lightningcast Dashboard

While doing the DSS for our event in Memphis (the Memphis Firework Preview Show 2) noticed a rather quick uptick in the Lightning V2 and eventually V1 probabilities about 45 mins or so prior to lightning strikes occurring near and around the site. This would give valuable lead time to any partner that was concerned about an outdoor event. It was made slightly easier to have confidence in this decision to mention an increased lightning threat especially looking at the line in satellite and on radar data.

– Sting Jet

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LightningCast Dashboard

Being this was my first time using the Dashboard, It took me a minute to figure out what I was looking at and which was V1 vs V2. But I believe the green line was V2, and it performed comparatively to yesterday in that it was quicker to react to the threat.

– Lightning McQueen

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Web based LightningCast for a DSS event

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

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LightningCast Comparison for Cabbage, Potato, and Bacon Festival near Hastings, FL (JAX CWA) on Wednesday May 7th

LC V2 did better with lightning cessation showing lightning probabilities dropping quicker as convection moved east of the DSS event which it title “HOME”. This allowed for more timely DSS updates to partners mentioning the lightning threat was diminishing, at least over the next hour or so. LC V2 also did better with storms to the south which we will talk about more below.

LC V2 showed higher probabilities for lightning quicker for developing storms near southern portions of the county warning area. V2 also lowered probabilities quicker once the storms temporarily pulsed down. I do believe one or both of these storms eventually pulsed up again after this though so it is possible V1 performed slightly better in this scenario by keeping slightly higher lightning probabilities.

LC V2 had tighter areal extent of lightning probabilities overall which was more helpful and accurate. May just need to be a little more weary of sensitivity to decreasing lightning probs too quickly for pulse thunderstorms in the summer.

– Ricky Bobby

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Day 3 observations

LightningCast/MesoAnywhere for DSS Event

We were operating as NWS JAX on 5/7/25. There was not a huge severe threat, but there were cells that produced a lot of lightning. Our DSS event was the Cabbage, Potato, and Bacon Festival in Hastings, FL (labeled as “home” in AWIPS). As soon as the   day started, there were cells within the range of the festival, with our primary focus on lightning cessation. One of the first things I noticed was that for the cells to the north of the cells, LightningCast v1 had a wider spatial extent of the probabilities than v2 for areas of decaying convection. I assumed this was because of the MRMS data as there were lower MRMS -10C reflectivities in the northern edges of the convection where the lower v2 probabilities were.  I was curious how that would impact the probabilities for the event as the convection began to decay there and how it related to notifying the event of an “all clear”.

Image 1: LightningCast data v1 vs v2 from 19:50Z to 20:11Z.

With respect to the event itself, using the lightning dashboard (image 2) was helpful. Probabilities both in v1 and v2 were high for the beginning of the day in the middle of all the convection. Probabilities started to decline around 20:15Z. Initially, v1 was declining faster, but by 20:30Z, v2 was declining at a faster rate than v1. There was still lightning within the 10 mile radius during these declines, but v2 it seems that v2 caught on to the decay a bit faster. This is also shown in the LightningCast loop from AWIPS (image 3) where v1 had a larger spatial extent to the higher probabilities for longer. I used LightningCast probabilities in my DSS messaging. When the probabilities were going down, I used a number in between each version for the probability I used in the message. I also utilized MesoAnywhere 1 minute Channel 13 data once it became available for us to monitor the potential for new convection behind the main cluster of cells. There was not much being shown, which made me more comfortable noting the event of an all clear.  Probabilities eventually did start to go back up after 21:15Z because there was a lot of convection to the north and south of the event.

Image 2: LightningCast Dashboard for the Cabbage, Potato, and Bacon Festival in Hastings, FL.

Image 3: Lightning Cast comparison loop from 20:43Z to 21:32Z.

Octane and Gremlin

Today was the first day that I used Octane. After getting some training on it from Jason, my first impression of it is that it would be a valuable resource for situational awareness for developing convection and alerting you to where stronger thunderstorms are. This could alert a forecaster to a cell that they may need to interrogate a little more. During warning operations, if radar data is available, I do not think that a warning operator would have enough time to use this in their data analysis, but the warning coordinator or mesoanalysis person would probably find this tool helpful. We went through a thought exercise about how we would use this tool when radar data is unavailable. During times like that, the radar operator would probably find this tool helpful because the storm top divergence and the speed sandwich offers information that radar operators look in radar when assessing thunderstorm strength. With respect to the individual options, I found myself using the speed sandwich more initially because I was able to infer the storm top divergence in a unit that I am used to. However, the more I get comfortable with the actual CTD units and colors, having it paired with the storm top cooling would provide me more information overall than the speed sandwich during warning operations. If I only had satellite data, I would probably be pretty liberal with my warning issuance. There was a cell near Juniper Springs around 22Z, where the speed sandwich and CTD tools were showing relatively “stronger” signals (stronger is relative since there were not many strong signals today). Looking at radar data (MRMS MESH, VII, dual-pol data) and knowing the environment, I did not think the cell was producing severe weather. I am not very comfortable just yet with the thresholds in these Octane products, but given the environment was supportive of marginal severe weather, I may have issued a warning in this instance. Both the SpeedSandwich and the CTD displays were indicating the storm was weakening though, so I also might not have either. As others have noted the last couple of days, the MedSmooth CTD was the one I preferred.
Image 4: Octane Speed Sandwich and Cloud Top Divergence and Cooling from 21:54-22:21Z=
Looking at GREMLIN for the same storm, it seemed to have picked up on the stronger signals of the specific cell and would be useful for pinpointing the storm with the highest “potential” in this instance since it was the one with the higher reflectivity values. I don’t know if I would make a warning decision specifically off of this product, but if I had it available in addition to other satellite data, I may be more inclined to issue a warning or an SPS if the environment is supportive of it.
Image 4: GREMLIN 20:31Z to 22:21Z
Unrelated to the previous storm, this was another snapshot I took of GREMLIN. There was an outflow boundary (not visible in this image) that was traveling southward and sparking new convection as it interacted with the sea breeze. A small cell that was relatively strong quickly developed to the southeast of the Jacksonville Airport. While reflectivities were picking up on MRMS, satellite didn’t pick up on it as quickly. GREMLIN did not catch this initiation.
Image 5: GREMLIN at 20:01Z.
There was a cell that developed along a outflow boundary very close to the radar. Satellite data was not really picking up on it with little cooling cloud tops so GERMLIN completely missed it.
-goldenretreiverlover
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RADAR DOWN IN DULUTH CWA

Without the use of radar out of Duluth more reliance was given to Satellite derived observations and satellite derived output.

Below is the OCTANE cloud top cooling and cloud top divergence product.  You may notice in an area of moderate but increasing instability there is convective initiation ahead of the main line of convection.  However, you can notice early in the loop that there is convective cooling indicated in the south-central portion of the CWA and the far SE portion of the CWA.  Notice how in the far SE portion of the CWA there is the purple shading indicating cloud top divergence.  And in south central portions there are “hotter” yellow and tiny red(s) (may be hard to notice due to scale) pixels indicating cooling cloud tops, but with no purple shading and thus no meaningful divergence at the cloud top.  This is indicative of orphan anvils. The moral of the story here is that without radar the OCTANE product heightens your attention to the cells in the far SE portion of the CWA, and this would be where to consider SVR or SPS product release, with the activity across South Central portions of the CWA failing to produce significant convection at this point in time despite moderate to strong instability.

Further southeast however notice that there is stronger instability over SE portions of the CWA, thus the OCTANE product is giving you a result which coincides with where there is higher instability (higher MLCAPE – see SPC mesoanalysis).

Lightning Cast continued to show high confidence of lightning over the next 60 min with the linear MCS moving into western portions of the CWA.  This lead to high confidence in forecasting lightning for a DSS location (Solana State Forest) during this event.

Steady behavior with the greater than or equal to 10 flashes in the next hour.

High probability of 1 flash of lightning in the next hour, increasing then holding steady

Here (below) is the Lightning Cast and GLM dashboard output comparing the forecast to the GLM flash count.  Note: the dashboard was down initially but came back online

Thus we were able to give a high confidence lightning forecast for DSS.

Here is the GLM Flash Extent Density at the time of the Lightning Cast 1 hour forecast.

– 5454wx

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