Resources to Assist with QLCS Tornado Warning Decision Making

I wanted to pass along some work that WFOs Springfield and St. Louis MO along with other partners have been doing relating to efforts to improve QLCS Tornado Warnings. These efforts have an overlap with some of the our HSLC CSTAR work.

Jason Schaumann, Lead Forecaster WFO Springfield, MO will be providing a presentation discussing some of this work during an upcoming conference call, likely in October. Prior to the October call, it would be helpful to have our group work through the links below including the SLS manuscript, Hollings website, Google Site, and YouTube videos. The two YouTube presentations are a great overview of all of the work over the last five years. During the call, Jason can help if anyone would like further explanation, or examples, or alternatively, he can demonstrate through a case study.

Snapshot of a reference for the Three Ingredients method for Meso Genesis, Intensification, and Tornadogenesis in a QLCS

Snapshot of a reference for the Three Ingredients method for Meso Genesis, Intensification, and Tornadogenesis in a QLCS

The initial work: Operational Application of 0-3 Km Bulk Shear Vectors in Assessing QLCS  Mesovortex And Tornado Potential by Jason Schaumann and Ron Pryzbylinski describes the three ingredients method for anticipating mesovortex genesis and rapid intensification. This methodology applies for both the cold and warm seasons. A statistical research project was conducted by a Hollings Scholar student to show the statistical significance of the three ingredients method.

Subsequently they worked to identify additional mesoscale and radar signatures that represent an increased probability for damaging winds and tornadoes from mesovortices. The recent culmination of these efforts includes guidance for issuing severe thunderstorm and tornado warnings for mesovortices.  Most recently, Michael Mathews from Bismark, ND developed a two page handout and video condensing and highlighting this work.

Jason constructed a Google Site which summarizes all of this work. Included on this site are two recent webinars that were given to Central Region (and a few Southern Region) offices. The first presentation covers the three ingredients method while the second presentation covers radar and warning strategies.

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1 Response to Resources to Assist with QLCS Tornado Warning Decision Making

  1. Matt Parker says:

    I am copying here some comments that were sent to a subset of the CIMMSE group in response to an earlier email on this topic. Mostly re-posting so that it is a part of the more permanent and widely-viewed record on this blog…

    I have never been a professional WCM, nor do I claim to have sufficient knowledge to sit down and issue warnings as well as folks in the NWS routinely do. But, I will add a couple of comments in the wake of the PECAN (Plains Elevated Convection at Night) project, during which I spent the better part of 45 days staring at MCSs as the radar data came in volume by volume.

    I strongly endorse the idea that the most threatening storms have this nearly-upright slope, which is often manifest as echoes with a large leading edge reflectivity gradient very close to the gust front (wind shift in Vr); this is their ingredient 1. An interesting thing we saw on occasion in PECAN was the development of new echo “reaching toward the gust front” from a seemingly upshear-tilted system (one where the echoes are generally well to the rear of the gust front). This process sometimes preceded development of a center of vorticity. The caveat to all of this is that, unless the system is moving directly toward or away from the radar, it can be hard to assess exactly where the gust front is. Close to the radar, a fine line may be evident. My only concern is that the presentation implies that this method can be used to determine where along the line one ought to focus. Unfortunately, different segments of an MCS are not sampled equally well by the radar.

    People have been saying for many years now that the 0-3 km shear component normal to the line is important (their ingredient 2). It’s nice that this is now available in one of the SPC mesoanalysis plots (although one has to dig a bit to find it). As mentioned by Steve Keighton in another venue, it seems unlikely to me that one can assess this in real time for all of the different orientations of various line segments within an active MCS. But, it might be helpful to have a mean line orientation and compute a mean line-normal component for reference. I would think it’s at least useful to know whether it is “well above threshold”, “near threshold”, or “well below threshold”. Perhaps this information nudges the forecaster toward or away from a warning (if well above or well below), but I am skeptical that it should be *the* determining factor in warning issuance.

    Perhaps the biggest “take away” message from PECAN is to really pay attention to these internal outflow surges (their ingredient 3). I would argue that these were probably the number one visible precursor to the development of vortices, gust front cusps, etc. Sometimes, they originate well back in the cold pool (i.e. well behind the gust front). They may primarily be associated with severe straight line winds at that point, but they often outpace the gust front and ultimately are associated with mesovortex development as they approach the gust front. I’m not sure I am 100% clear on the dynamics yet, but we talked about these critters *a lot* during PECAN. Of course, once again, you have the problems with radar sampling. In addition to sampling only the radial component of the wind, there is the issue of beam height at range. We had examples in PECAN of impressive 30+ m/s surges in the base scan at heights of 600-800 m AGL, but with no severe winds at the ground as we drove mesonet vehicles directly beneath the surge.

    This is interesting stuff, and it’s reassuring that a lot of independent groups seem to be converging on the same ideas. It would be great if we could have these folks present on one of our calls!

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