Remember to look underneath the hood

Here’s another example where a casual look at ProbTor might cause some confusion. Flow parallel to the boundary across the OKC metro eventually won out and the semi-discrete cells merged into a messy, slow-moving mess shortly before 22z. At 2148z, ProbTor peaked at 74% for the mass of convection just NE of OKC. However, KTLX velocity showed no immediate areas of concern. The answer to the high ProbTor was found in the 0-2km merged AzShear product. AzShear showed an enhanced area of shear to the NE of OKC near Spencer with generally convergent and broad flow. This is a good example of how ProbTor can be useful in operations: it quickly highlights areas for further investigation that can either be confirmed or thrown out with a very quick interrogation of the base data. In this case, ProbTor worked well, it was just biased by the abnormal/noisy AzShear data.

–Stanley Cupp

2148z KTLX base refl (top), base velocity (middle), and 0-2km AzShear (bottom) with 74% ProbTor contour overlaid on each

Why hello friend – merging supercells into a single ProbTor Object

 

Here a strengthening southern supercell invaded the personal space of its “more aged” northern neighbor. The merger did not change the  ProbTor values of the original, stronger storm (90%) but did eventually show a slightly lower value (87%) despite the southern storm becoming more intense in rotation. There were only subtle differences noted in the ingredients and nothing stood out as to why the Prob values dropped.

As for the new mesocyclone algorithm (xmda) the strength rank jumped to 25 (max value) at 23:32. It is difficult to follow the individual storms in the attribute table since they jump from page to page and are ordered by ID versus strength. Having the cell ID color coded at certain values (e.g. above 10 colored yellow, above 15 colored blue, etc.) would help more quickly discriminate the strongest mesocyclones, especially if you have to move to another page. ProbWind (lower right panel) continues to be very high for these supercells (consistently >90%) although no wind reports were received by SGF.

0-2km AzShear/ProbTor (UL), 3-6km AzShear/xmda (UR), HI/ProbHail (LL), Z/SRM/ProbWind (LR)

CPTI example

CPTI closely followed the 0-2 Az Shear product in both shape and intensity. This included all velocity time matching errors. These time matching errors decreased the usefulness of the product each time they were seen. CPTI prob of highest winds appeared more useful than the lower thresholds, better enhancing where the threat of strong winds was actually located. Lower thresholds (example at end of loop) appeared to be too broadbrushed for applicable use.

HWT day 2: 19:10 GLM and AzShear observations of Missouri tornadic supercell

Feature following zoom showing the GLM pulsing phenomena associated with intensification/weakening of a supercell in OK/MO. During the third pulse, a TOR warning was issued.

Case of CPTI values on a confirmed tornado near Miller, MO. No confirmed damage estimates yet, but TOR was confirmed at this time visually and with a TDS

Lightning jump preceding a tornado and then confirmed touchdown in MOEvent Density over the same cell

Minimum Flash area showing updraft core

 

Average Flash Area

 

This is a case where AzShear overdid the tornadic threat This supercell had a circulation that never really tightened up. ProbSevere also vastly overestimated the tornado threat, likely due to nearby storm interactions and mergers. When convection gets messy, can we rely on these products as much?

 

The two images above compare a 4 panel of 1 min GLM data (left four panels) versus 5 min data (right four panels). While the 5 min data was much smoother to view from an animation and trend sense, the 1 min data did provide some fine temporal resolution help during periods of rapid storm intensification preceding this tornado warning.

The above two loops compare 1 min looping (top 4 panel) versus 5 min looping (bottom 4 panels). In a loop the ‘flashy’ nature of 1 min data makes it less desirable in operations, however manual toggling and advancing still make this data useful.

 

Max Value Readout for GLM in upper left of screen?

 

GLM FED maxed out at 160 fl/5-min and TOE at 580 fJ on this cell in southern MO. It would be nice to have the maximum value, at least for the FED and TOE products in the upper left corner like the ground-based networks have. This would also help with quantifying things such as lightning jumps or quickly comparing two cells.

GLM FED (UL), AFA (UR), TOE (LL), RLA (LR)

— SCoulomb

NUCAPS Modified Sounding Analysis

Wichita Falls tornadic environmental data using NUCAPS Modified Sounding.  NUCAPS sounding surface data had temp/dewpoint of 73/68, looking at surface obs temp/dewpoint range near the NUCAPS point sounding was 74-76/69-70.  Therefore modified numbers were in the ball park.

NUCAPS 700-500mb Lapse Rate Gridded Product did a decent job with mid lapse rates across southwest Oklahoma showing a favorable environment for severe thunderstorms.

 

Wide angle view of GLM

 

This wide view of GLM shows the typical small number of very large flashes in the trailing stratiform region across KS and MO. Smaller more numerous flashes, also brighter in TOE exist along the front across central OK into northwest TX. The more discrete cells along the stationary front in southern MO are also evident with the greater flash rates, smaller flashes and brighter appearance in TOE.

GLM FED (UL), AFA (UR), TOE (LL), RALA (LR)

— S COULOMB

GOES-W & GOES-E GLM comparison

 

Looking at GLM for GOES-W in Full Disk (L)  and GOES-E in meso sector (R) the flash extent density and average flash area compare well to one another. Max FED values were 62 and 64 fl/5-min respectively. They also showed similar overall footprint with even the smallest flash values. Parallax is obvious with the peak  values separated by ~15 mi at this longitude.

GLM FED from GOES-W full disk (UL), GLM FED from GOES-E meso sector (UR), 10.3 um from GOES-W full disk (LL), 10.3 um from GOES-E meso sector (LR)

— S Coulomb