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.
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MesoAnywhere showing the orphan anvil.
