NUCAPS Procedures Usefulness

The NUCAPS Quick  Guide from JPSS includes a few procedures. Here I show the utility of a few of those procedures for combining GOES Satellite data and NUCAPS data.

This procedure plots 400-200mb relative humidity and GOES-16 water vapor. You can see the representation of the dry air across the northern US and the systems in the Plains & southeast.

Another procedure compares GFS, HRRR, and NAM lapse rates with the NUCAPS lapse rate info. This is a good check to see if model lapse rates are performing well or where they need to be taken with a grain of salt.

Another procedure plots 850-300mb RH and low-level water vapor. The product shows the system in the Plains and the system in the Ohio Valley. Drying is also obvious in the southern Great Lake and North Dakota.

I like the procedures provided in the JPSS Quick Guide. I am starting to understand the applicability of the NUCAPS data little bit more. These procedures are helpful in contextualizing the provided data fields.

-Atlanta Braves

AllSky as a good proxy for dryline location and CI

The AllSky Layer Precipitable  Water product showed utility in identifying and tracking the dryline as it moved into the Lubbock CWA. The dryline entered the CWA at about 1930 UTC.

Coincidentally, the KLBB radar shows convection initiation around 19:30 UTC as well.

And the convection continues to develop:

The AllSky product remains a very useful tool for situational awareness and 2-D environmental familiarization.

-Atlanta Braves

Single-Radar AzShear Tornadogenesis Success

Single-radar AzShear does a really good job of identifying preferred locations of circulation along a QLCS. The bullseye started as an elongated area of enhanced AzShear and then converges into a more concentrated area. This product provides a helpful heuristic for identifying tightening circulations in the midst of noisy velocity data with less-clear signatures.

One can easily see the congealing AzShear bullseye before the circulation tightens the tornado starts.

On the contrary, the Merged AzShear product demonstrated some latency issues that would lead to less confidence in circulation tightening.

This image, taken at the same time as the KEOX AzShear product, shows several unorganized areas of enhanced rotation right before the tornado started in the merged AzShear product. The tightening circulation is an important precursor to tornadogenesis and the merged product seems to struggle. -Atlanta Braves

Single-Radar AzShear Product Showing Clearer Signal Compared with Merged Product

The single-radar 0.5 degree AzShear (left pane) shows a coherent area of high values associated with the velocity couplet (bottom right pane). Compare this with the merged product (upper right pane). The merged product shows a few different maxima in AzShear which is probably associated with the multiple radars and beam heights that are used to make the product. The single radar product also tracks the velocity couplet better in real time and is not subject to the lag in the merged product due to the multi-radar processing.

Ron Dayne

Lightning Jump in GLM FED, but not Earth Networks data

Storms continue just after 7pm near the Oklahoma/Texas border. A currently severe-warned storm saw a substantial and rapid increase in lightning activity observed by the GLM Flash Extent Density product. However, the ground based lightning network did not follow the same trend and remained fairly steady. The ground based data is more reasonable considering the storm did not experience any sort of significant strengthening during this time period. Earlier discussions with lightning detection experts suggested the low GLM FED count may be due to the location of lightning within the storm updraft region, which could impact how well GLM can sense it. That is difficult for the typical operational meteorologist to consider in real-time since it goes well beyond current training, and leads to decreased forecast confidence in the lightning data.

Dave Grohl

Mesocyclone Detection Algorithms Performance on Marginal Supercell(s)

A cluster to 2 merged supercells traversed across northern Oklahoma this evening. The loop below shows the performance of all three mesocyclone detection algorithms.

The legacy MDA performed the most poorly of all 3 detecting several inaccurate mesocyclones with inconsistent tracking. The DMD performed remarkably well in both tracking and intensity on the main meso  The NMDA experienced occasional dropouts where data was unavailable, but also performed pretty well on this storm. It particularly detected intensity well through the lifecycle of the meso.  The AzShear product also tracked the main mesocyclone very well. The DMDA performed best of all three for this storm  but the NMDA also showed promise. -Atlanta Braves

ProbTor/ProbSevere Impressive Performance

There were 2 adjacent supercells heading into the Tulsa CWA and ProbSevere kept them as  separate objects (correctly) despite their proximity. This is a great sign. Additionally, the ProbTor product effectively differentiated between a tight couplet (north, 70% ProbTor) and a weaker couplet (south, 34% ProbTor).

This case shows the ability of ProbSevere to differentiate storms with distinct features despite close proximity. It also shows that ProbTor is doing what we think it should based on velocity features. -Atlanta Braves

TDS CPTI Evaluation

A tornado produced a TDS in the SW part of the Tulsa WFO CWA at 21:44Z. Maximum TDS height was ~6kft.

The CPTI adequately represented an increase chance of a strong tornado (18-20%, top left).

It appears this CPTI did not have the same issues with effective STP like yesterday’s St. Louis tornado did. I like this product a lot! -Atlanta Braves