What’s even better than AzShear?

AzShear + DivShear = Velocity Gradient

Below is a look at AzShear down low with an approaching QLCS. Fairly noisy right?

Here is another view using DivShear – in other words, divergence along a radial similar to how shear is computed across radials. The convergence (i.e., negative divergence) shows up nicely, eh?

Now combining those fields together with Velocity Gradient, things really start to jump.

Look how well DivShear works with MARCs , too:

Certainly better than AzShear when it comes to mid-level convergence…

And then putting them together for Velocity Gradient…



Now, closer to the QLCS “summit”, we see fairly coherent DivShear…

And this is how Velocity Gradient shows it.

Hoping to show some extremely cool results with these fields involving a QLCS mesovortex later in this case if time permits…

#MarfaFront

Low Level AzShear (0-2km) correctly identified an area of rotation associated with the western supercell, however, AzShear was also saturated above 0.01 along the leading edge of the bow echo in the MCS as well. While it’s good to drawn attention to the latter area, as it was producing severe wind (61kts), it was not tornadic.  Additionally, there is some noise in the merged LL AzShear that wouldn’t exist in the single radar AzShear. I believe single radar AzShear would perform better in this situation.

-Tempest Sooner

As I discussed in my previous post , tornadic damage should be focused at the edge of the AzShear maximum. Below is an example from the case we’re studying. The negative AzShear region is not super defined here and I’m wondering if it’s due to excessive noise and/or oversampling from being so close to the radar…

#MarfaFront

Those of us who use GR2Analyst already have access to AzShear via its NROT product. I stated elsewhere that the negative values are important, and here I’ll attempt to explain why.  Below is a schematic of a Rankine vortex, which is akin to a rotating cylinder. Radial velocities are maximized at the edge of the cylinder and then drop off as an inverse  function  of range.

We know azimuthal shear is positive across the entire “cylinder”….

What about just outside the cylinder? If you look closely, you’ll see that there are *negative* AzShear regions on the radials that are just outside of the max/min radial velocities positions…

Putting it all together and thinking of azimuthal shear as a running average of shear as we move across the radials, we get a plot of AzShear that looks something like the black trace below.

We see slightly negative AzShear regions flanking the AzShear maximum, which would be observable for a well-sampled mesocyclone, such as seen on the right hand side of the image below…

Also notice in the figure above that the maximum inbound/outbound velocities line up with where AzShear crosses zero.  Now, let’s pretend we have a rear flank downdraft or RIJ surge by boosting the “inbound” side of the circulation…

Now what does the new AzShear trace look like?

Well, we see more of an AzShear “couplet” as both positive *and* negative shear increase on either side of the surge. The maximum winds are still occurring where AzShear equals zero and this is located directly in between the AzShear maximum and AzShear minimum in conjunction with the center  the surge.

I’m firmly convinced that looking between these two features is an effective way to pinpoint where the most damaging wind will occur, whether it’s tornadic or straight-line. For the smaller tornadoes that most of us get, the southern edge of the AzShear maximum is a sweet spot that has the cumulative effects of rotation, translation, and inflow to maximize winds.

#MarfaFront

Just before tornado formation (as in just before CC hole develops) on leading discrete supercell, Az Shear product quickly ramps up in values and would be useful in getting warning forecaster attention that there is a strengthening low-level circulation there.

Stepping back and looking at the squall line, the Az Shear product quickly allows the warning forecaster to visualize the s curvature in the squall line, and quickly isolate the central segment of the squall line that is becoming more favorably oriented with the environmental shear. Here I was able to more quickly focus attention on the segment of the line that would go on to produce a tornado.

A couple of scans later, the AzShear quickly trended up before true gate-to-gate couples appeared in the velocity product. This would help the warning forecaster get a jump on the areas of tornado formation.

Viewing angle and distance from the radar definitely important. In the images below MXX is much closer to a QLCS tornado and viewing from behind the line. While EOX is south of the line looking down the length of the line, and viewing from a greater distance. Here the low-level QLCS circulation is much more evident in MXX, while it gets lost on EOX. The area of interest is marked by the white circle on each image.

Felt the main benefit of this product may be for QLCS tornadoes, and could extend warning lead time. In the example below, a mesovortex along the line is more easily identified by viewing the AzShear product over the raw velocity data. This will allow the warning forecaster to more quickly identify the important areas along the line that will need monitoring. By expanding the color table at the top end of the color curve, it was easier to monitor the trends in the strength of the circulation. This combination could allow the warning forecaster to more quickly identify a circulation and start drawing up a warning while monitoring the trend of that circulation as input to the warning decision. Overall feel this could really help forecasters extend warning lead times on QLCS tornadoes by a couple of volume scans. This is a huge help as these tornadoes are already the hardest to warn on with lead time.

— warmbias —

In one case of a tornado embedded within the QLCS, the AzShear signatures  from both radars were nearly 100 km away. In both instances, the signature was displaced northward from the tornado path. From KEOX, the tornado path was 107.8km from the radar and was looking at approximately 1.8km up in the storm. From KMXX, the storm was 89.9km from the radar and looking at 1.4km in the storm.  Something to consider for training is the distance from the radar and any tilt from the storm.

Also interesting, is that KMXX, looking slightly closer and lower, shows a stronger AzShear signature than KEOX (0.016 s^-1 vs 0.006 s^-1). So, still a best practice is looking at multiple radars if looking at single radar AzShear, or look at the MergedAzShear 0-2km products. However, it has been noted that the mergedShear products may be more useful for QLCS type storms, vs. supercell storms.
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A little while later…

A long-tracked supercell ahead of the line exhibited very high AzShear values early in its lifetime (as high as 0.03 s^-1), but as the storm moved away from the radar, the AzShear values tended to decrease. At first, it was thought this was merely coinciding with the distance from the radar (160km at time of first image below) and how high in the storm the radar is looking (3km), however, there may also be some information about the strength of the tornado at that distance. At 160km, the AzShear strength dropped to around 0.006 s^-1. However, a short time later, there was another strong AzShear signature (>0.01s^-1) just south of there, that was also associated with a tornado path. This signature was also at 160km from the radar. Curious if it could be surmised that the northern long-track tornado was not at strong as the southern shorter track? Also of note, the southern signature was again north of the assessed tornado track.

-Tempest Sooner