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

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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

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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

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LightningCast for Convective Initiation and IDSS

LightningCast V2 did a great job predicting lighting development with developing convection along a frontal boundary in northwest Iowa. It outperformed version 1, as shown by the loop and images below.

Animated GIF showing LightningCast V1 (top) and V2 (bottom) with the day cloud phase darkened to show detail. The ENI total lighting (yellow CTG flashes, white cloud flashes) is also displayed.

At 1946Z, V2 has a higher probability of lightning (50%) than V1 (30%).

This trend continued throughout, and at 2016Z the first lighting strike was detected. That’s 30 minutes of lead time, which would be helpful for outdoor event IDSS.

LightningCast at 2016Z with initial cloud to ground strike shown in the yellow dash.

– Updraft

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LightningCast Dashboard

One of the more useful features for DSS messaging today was the Dashboard Request Form for values at our State Track Meet. Since we were operating under the assumption that the go or no-go threshold for this event was lightning within 10 miles, I liked using the dashboard but isolating the Max P 10-mile radius line in pink.

One note of feedback I had was to add some context for what we’re looking in each line at by noting where the data comes from in the legend. I was able to verbally ask a visiting scientist exactly what each line meant and where the data comes from, but this may not always be an option. The suggestion we came up with was adding (5-min, CONUS) and (1-min, MESO) to the legends circled in red so that it’s clear that the 5 minute data came from the CONUS satellite and the 1 minute data comes from one of the mesosectors.

– millibar

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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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