Basic OCTANE Cloud Top Divergence Comparison

 This is a basic comparison between three options for the OCTANE. The top animation is No Smooth, the middle is Medium Smooth, and the bottom is High Smooth.  For starters, I do like the looks with the smoothing, it is easier on the eyes and rids of any excess noise.  I feel this helps to recognize trends easier and remain focused on those trends through the animation.  In this loop, following the regenerating updrafts west of College Station and Snook, TX, was somewhat easier to follow on either the medium or high smooth.  Smoothing out the excess noise around the updraft helped remain focused on the primary portion of the storm.  The warning issued was based on radar data, but could imagine the Cloud Top Divergence being a helpful tool in warning decisions if radar data wasn’t available. It certainly is a “confidence booster” or a nudger if you’re on the fence for a warning or not. It would be interesting to correlate the CTP (to hail size, wind, and/or if a tornado was produced. Obviously this would take some extensive research.  

- Podium

Houston CWA May 6th event.

 Started out issuing a warning for parts of northwest Houston’s area based on info from the Flash density product.

3:06 PM. Using Octane, noticing a cluster of convection that is developing and becoming more interesting for warning purposes.

3:38 PM Severe Tstorm with tornado warning out. Special feature noted on Octane Speed Product where the updraft was reisting ambient wind flow as the storm intensified noted by cyan colors on LA/TX state line near Shreveport.

-Jolly Rogers

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

LightningCast v1 vs LightningCast v2 5/5/25 21:26Z-22:21Z

 The cell I was observing was producing infrequent lightning for much of the period in the loop with probabilities in v2 staying consistently higher than v1 before and after the lightning strikes. v1 decreased to near 0% at 21:41Z right before a strike occurred at 21:56Z although the probability in v1 increased to 10% at 21:46Z. v2 probabilities remained relatively consistent during that time frame. It seemed that with the MRMS data, it had enough reason to continue the probabilities even though the lightning was infrequent. From a forecaster's perspective, this would give me more confidence that the storm was persisting and was continuously capable of producing lightning whereas v1, I might think that (if only relying on the LightningCast), the threat was diminishing.

4 panel comparing LightningCast v1 and Lightning Cast v2

-Golden Retriever Lover

LightningCast V1 & V2 Differences in ABQ

GOES-East LightningCast Version 1 seemed to pick up on lightning ahead of LightningCast Version 2 (MRMS-trained) for the cell in the southern portion of the ABQ domain (bottom-middle of screen), with higher probabilities (75% + for V1, 50%+ for V2) at 1916 UTC 05 May 2025. However, once the GLM FED detected lightning, LightningCast V2 saw a more expansive 75% contour. A theme I seemed to pick up on was that LxCast V1 would have higher lightning detection probabilities than V2 prior to initiation, but V2 would have a greater footprint of higher probabilities thereafter, more accurately capturing lightning once it was occurring. V1 probabilities seemed to fluctuate more often than V2 as well. 

LightningCast V1 and V2 output in the ABQ WFO area at 1916 UTC and 2006 UTC 05 May 2025.

-May052025