GOES 16 – Full Disclosure

Ok, last post….honesty time.

I didn’t make this a secret in my application that I had been out of meteorology for about 4 years between 2014-2018. During that time, GOES-16 launched. As I returned to broadcasting, I didn’t adequately spin-up on the new capabilities of this new generation of satellites. I was aware of the spatial and temporal resolution improvements of course – what meteorologist – currently working in or out of the field, didn’t get excited about 1 minute imagery?

However, I wasn’t aware of some of the RGB combinations that I’ve been exposed to here at the HWT. The features that can be picked out by applying coordinating colortables to multiple channel views is simply astounding. I’ve used the simple water vapor, day cloud phase distinction, day convection, differential water vapor RGBs this week….I’ll be making a phone call to my broadcast weather vendor. I know I’ll need to get some other broadcasters on board with me to lead a charge, but count me in. Until then, I’ll be livin on the CIRA RMMB Slider site!

Color (RGB) Me A Fan!

-icafunnel

NUCAPS FCAST

Knowing that the NUCAPS FCAST information was in today for the first time this week, I decided to do some analysis of the fields. Initial thoughts are that the missing blocks of data (not sure if that is typical – more visible in the CAPE field in top image – similar data holes observed in LCL, LFC and EL) make it hard to have confidence in it at first glance.

CAPE (Top Image)
NUCAPS FCAST CAPE data isn’t good in the pre-storm environment along the LA coast. RAP13 initialization is overlayed for comparison. RAP13 values are 2500-3500+ and much more representating thatn the NUCAPS values that in some cases are less than  500 ahead of the line.

CINH (Lower Image)
While these values appear to be more closely representative compared to the RAP13, the inability of the product to adequately represent the boundary layer at times during the week don’t provide me much confidence for these surface based stability parameters.

-icafunnel

Warning Decision Influenced by ProbSevere

Since our shields have been engaged all afternoon I decided to look at a storm to our east. Below are a series of reflectivity images from the three lowest scans (0.5, 0.9, and 1.3)…

I won’t lie to you, if I were back in my home CWA I would have probably issued a SVR based on these scans, but I decided to hold off on issuing one today until we got close to 90% probabilities to see how ProbSevere did.  So what did ProbSevere show? Here is a sample of various MRMS products overlaid with ProbSevere contours…

And here is a time series for this storm looked like…

These trends looked pretty impressive, with ProbHail peaking around 86%. The increase in probabilities make sense, with MESH peaking around 1.4 in (below in purple).

We will have to wait and see if my decision to not issue a SVR based on a ProbHail is justified, but based on the lack of any reports, I think it may have been a good call.

UPDATE…The storm in question got one severe hail report.

Four Views of TPW

After making some adjustments to the color scaling, we’re able to mix model and analysis products of TPW.   The GOM was mostly clear, while clouds covered most of the land.  A very moist airmass was onshore, the Hammond LA GPS site measured 2.25″ of TPW.

The GFS and HRRR forecasts both indicated this maximum.  The All-Sky LAP also did well, although it’s field is a reflection of the good GFS forecast.  The Merged TPW did not generate these very large purple values (> 2″ of TPW) except in a very small area.  The polar orbiter TPW retrievals used in Merged TPW must not have sampled these large values to advect in.  The operational blended TPW (which relies heavily on GPS sites for the analysis over land) also showed a maximum.  This points to the possibility that including the surface GPS network into Merged TPW and All-Sky LAP might be a way to increase the precision of these analyses.

Cloud Mask from CIRA Merged TPW (blue = clear; yellow = cloudy)

 

Four Views of TPW along the Gulf Coast at 19 UTC 09 May 2019: Upper Left: CIRA Merged TPW: Upper Right: All-Sky LAP. Lower Left: GFS 6 hour forecast @ 18 Z, Lower Right: HRRR 1 hour forecast @ 19 Z.

Analyses and forecasts all agreed well on the drier air over the central GOM.

 

JohnF

Here’s an exciting non-case. Hooary!

In this example, Houston County in the far Northern HGX CWA was in horrible radar coverage with 0.5 degree radar scans over 12kft AGL. With the success of GLM FED predicting severe storms earlier in the day this was used to give confidence NOT to issue a warning for this area, despite slight bowing in the sloppy reflectivity and an abundance of activity in the ENTLN network.

#ProtectAndDissipate

Tornado Warning Prompted with Merged AzShear

Radar imagery f/ KGRK showed rotational low-level organization within the QLCS. While ProbSevere was putting near 80% for the wind threat with and increase to a 9% for a tornado threat. The Merged AzShear product was showing strong 1D pseudo-vorticity in the area of interest and was used to push the SVR warning w/ Tor possible tag up to a Tornado Warning. Immediately after issuing the warning the circulation seemed to fall apart, however, a couple minutes after the warning a report of a wall cloud with a rope tornado came in through the chat. Lead time may have been nill (also due to not having a Text Workstation up yet), but the warning seemed to have verified thanks to the dependency on the AzShear product. With a single-radar AzShear in operations it would have been possible to increase lead time.

UPDATE:

Going back and looking at the GLM data showed intensification of the cell which spawned the reported tornado before genesis (or at least before the report). GLM FED shows the previously warned cell to the north fading in strength and the intensifying updraft of the cell to the south that prompted a tornado warning.

#ProtectAndDissipate

 

Using Single Radar Shear w/ Merged Shear

Here is another example as to where high single-radar Az Shear and Merged shear values remain significantly high while velocity values falsely indicate the storm may be weakening. Using Az Shear coincident with Merged Shear data would result in myself (as an operational forecaster) maintaining focus on what is likely still a significant storm, even though the overall velocity data no longer looked as impressive.

Noticed that the NMDA was glitching out in some of the upper levels of distant storms. Ironically, despite all the false detections, it didn’t identify some of the actual rotations, distant or within the CWA that were ongoing.

#ProtectAndDissipate

Merged AZShear picking up on the low-level rotation nicely!

(Don’t know why images are being weird here)

#ProtectAndDissipate