Author: Kevin Thiel

Optical Wind Inferences

Posted in Optical Flow Winds on by Kevin Thiel.

The “All” winds display setting was useful in combining the multiple layers of wind data, however, without a proper understanding that the winds displayed (and subsequently shaded), a user may incorrectly infer regions of convergence/divergence. I found it useful to ‘build’ the wind layers from the top of the atmosphere (100-50mb) down, to see in which layer the winds displayed where located.

Circled in red are areas that one might incorrectly infer the presence of strong speed divergence, when, while divergence may be present, the winds displayed are at different levels of the atmosphere based on the level of the optical wind sensing. Perhaps there is a way to color-code the wind barbs to correlate height / pressure level (Red for surface with a gradient toward blue for 100mb, or so)?

– Guillermo

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NUCAPS Sounding comparison to Observed Sounding

Posted in NUCAPS on by Kevin Thiel.

Noticed an across the board temperature discrepancy between the Observed Sounding at KJAX and two of the NUCAPS soundings from the afternoon pass of NOAA-20.  Looked at two different NUCAPS soundings which straddled KJAX.  The morning sounding at KJAX (12Z) showed a typical morning, warm tropical but capped sounding.  The two NUCAPS soundings were from six hours later showed a surface change that would be expected but then showed decent cooling from the morning through the entire column.  The image below shows the two NUCAPS soundings, one is in focus (red/green), the second NUCAPS soundings is the drab color and the observed sounding is in blue.  This shows the two NUCAPS soundings to be very similar and follow each other well but are also a few to several degrees cooler than the observed sounding. 

While I would expect some areas of the column to cool with a sea breeze front coming through, but not the entire column.  When I see this type of discrepancy, it makes me not want to trust the NUCAPS sounding in this case as it does not seem to make much sense with the ground truth of the actual measured RAOB.  Of note, when the NUCAPS sounding was taken, the line of sight was free of clouds and the “dots” were green; however, there were thunderstorms to the north and west of KJAX and they had an outflow boundary approaching the area rapidly.  Could this have made a difference?  I don’t know but it is worth noting this did occur.  Also, we also noted the NUCAPS soundings for this area were all cold in comparison to the morning RAOB.  Looking further west to KTLH, the NUCAPS soundings and the observed soundings looked much closer and made a lot more sense.  So, could this be a marine layer influence?  Could this be just a bad batch?  Could this be a bad thermometer and wet bulb sensor on the actual RAOB?  All valid questions that I can’t answer but put here as possibilities that can’t be verified.  

Of note, we also looked at the differences between the KSC 15Z sounding and the afternoon and the afternoon pass of the NOAA-20 NUCAPS soundings.  These two were much closer and seemed to be much closer together.  Also note, the time difference between the two soundings is only 3 hours in comparison to six.  The image below is the KSC sounding comparison.  The sounding in focus is the actual KSC RAOB and the NUCAPS sounding is in the background.

-Strato-Dragon

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Optical Wind, GLM, and ProbSevere Use in Convective Environments in North Carolina and South Carolina

Posted in GLM, Optical Flow Winds, ProbSevere on by Kevin Thiel.

Looking at multiple levels of optical winds can be useful in analyzing the amount of wind shear over an area in near-real time. In this case, the tool shows limited wind shear, so one would expect storms to be a bit more short lived. Would it be possible to add wind shear fields directly into this tool for quicker analysis?

Optical winds for the ILM CWA on 6/15 at 18Z showing little difference in the winds between the 800-600mb and 600-400 mb levels.
4 panel of the GLM data at ILM around 19 UTC illustrates Flash Extent Density (top right), Minimum Flash Area (bottom left) and Total Optical Energy (bottom right). We adjusted the colormap of the minimum flash area so that we could identify the updrafts more easily since the minimum flash areas were under 100km^2 and the default map was set to cover images up to 2000km^2. This allowed us to identify which storms featured the strongest updrafts which when combined with data from the Flash Extent Density, we could watch for storms that were strengthening and thus posed a greater need for a warning.

Three Body Scattered Spike & ProbHail

Three body scattered spike is visible in the storm in the top right panel.
ProbHail shows values of ~65% when the three body scattered spike appears with MESH values over 2” supporting the likelihood of at least severe size hail in the discrete cell.

Watching the meteogram on this storm, we can see the probhail values jumped up to 65% over the last 15 minutes. It’s probably best to have ProbHail values of 60% or more last for a few volume scans because that suggests the residence time in the hail growth zone is long enough for hail to grow and become 1” in diameter or larger.

–Earl Grey Tea and Fear the Shear

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GLM Lightning Data & Convective Insight

Posted in GLM on by Kevin Thiel.

Assessing the various GLM lightning products, I found the MFA and FED particularly useful in correlating the more active thunderstorm core / updraft areas. TOE was useful, but maybe a slight change in color scale may help to better identify those very active convective areas. (perhaps the sharper color gradient change could start at a slightly higher value than currently)

Upper Left: FED img + Flash Point + ENTLN; Upper Right: TOE img + Flash Point + ENTLN Lower Left: Radar img + ProbSev + Flash Point + ENTLN Lower Right: MFA img + Flash Point + ENTLN

The GLM flash point data didn’t show as much ‘clustering’ as I had expected to see, as compared to other surface-based data sources (ENTLN). Is this related to a data display density or a more sensitive surface-based lightning detection? However, due to the parallax correction, the flash point data did line up with fairly well with active convection, although there were a few flash point detections well displaced from any radar reflectivities (see bottom left)–perhaps related to stratiform lightning?

– Guillermo

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GLM in Northern Florida

Posted in GLM on by Kevin Thiel.

Comparing the Flash Extent Density to base reflectivity in northern Florida, we noticed an area of exceptionally high flash density just north of the best convection. Adding flash points (parallax corrected) to the radar image and they were more where one would expect in the storm. This indicates a parallax issue with the Flash Extent Density. This is a good example of where the flash points can be a good sanity check when interrogating a storm.

Base reflectivity and flash points (left) and five minute Flash Extent Density (right).

– Earl Grey Tea and Fear the Shear

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Florida lightning

Posted in GLM on by Kevin Thiel.

Using GLM for an IDSS event  allows for great flexibility and confidence in providing warnings for decision makers.  In the image below, this shows a complex organization of thunderstorms. In this case, a lightning alert or warning for them.  In this case, since the thunderstorm structure is much more complicated, it is unlikely an all clear would be provided for some time.  It is likely this would be persistent through the afternoon as the surface front is pushing the sea breeze front back toward the coast and keeping the activity nearly parallel with the coast.   In this example, the FED product does provide the forecaster a good idea of the forward extent of the which is to the south and east, despite the fact the upper level winds are pushing the avils to the north.  The lightning points are also helpful to get an idea of where the potential return strokes are actually reaching the ground enveing though the GLM “can’t” actually 100% determine this but just based on the probability.  

Point flashes also provide the user with an idea of the size and potentially the ability to identify which core the lightning originated from.  Not sure how well this will work or if it will work but just a thought.  Think more work and or research will be required before we can say one way or the other if this will actually work.

– Strato-Dragon

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Using NUCAPS (Modified & UnModified)

Posted in NUCAPS on by Kevin Thiel.

Advantages to SHARP.py vs. AWIPS NSHARP.

NSHARP – AWIPS (Advantage is being able to see both modified & unmodified soundings

SHARP.py (Advantage is the cleaning picture and able to display two or more soundings on the same backgrounding – Skew-T)

How two passes of the NOAA-20 near the same location can be used to determine the small changes in the atmosphere.

(Green/Red – Moisture/Temperature Profile at the 1842Z Pass)

(Green/Red – Moisture/Temperature Profile at the 2042Z Pass) Note the increase in moisture in the boundary layer which corresponds to the increase in CAPE.

These two comparisons of the soundings within two hours of each pass showed how well the NUCAPS can be used for small differences in atmospheric moisture and instability.

During this time period, there was a pronounced dry-line west of the sounding, and a synoptic scale front approximately 100 miles to the north of this NUCAPS sounding.

Note where the dryline (Cumulus line over northeast Mt) was located and how you can use NUCAPS to show how capped or uncapped the atmosphere becomes in the afternoon with the NOAA-20 passes.

– wxboy65

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Using Optical Wind Flow

Posted in Optical Flow Winds on by Kevin Thiel.

Convective storms that developed across northeast Montana showed the speed and direction of the outflow. Note the divergent flow outward from the overshooting top, to the outer parts of the anvil. This image also provides the pressure level associated with the wind speed and direction of the flow aloft. This can help determine the strength  and possible intensity as it evolves through the life cycle of the convection storm.

– wxboy65

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Use of Cloud Phase Distinction RGB to anticipate convective initiation over Western Dakotas and Eastern Montana

Posted in GOESR, ProbSevere on by Kevin Thiel.

Some members of the 12z Thu Jun 10 HREF run were a bit slow in initiating convection or too far east in developing convection over the Northern Plains. The NSSL WRF-ARW was closest to reality with respect to exact timing and location. A special 18Z RAOB from Glasgow (GGW) MT and the Cloud Phase Distinction RGB proved to be very helpful in showing convection was going to develop earlier than anticipated by the HREF guidance. The 18Z RAOB from GGW (below) showed weak CINH values, while the Day Cloud Phase Distinction RGB (second graphic) showed an agitated cumulus field that was becoming quickly glaciated (single cell with yellow cloud top near the 93/61F sfc obs) indicating deep convective development was imminent.

Once deep convection initiated, single channel ‘Clean IR’ imagery and Day Convection RGB became more useful in determining updraft strength. These two products can be extremely useful in severe weather detection and warning decision making especially in absence of radar and/or lightning data or when used combined due to its faster temporal coverage (1-min in meso sector vs 5-min from radar).

The image above shows updrafts getting stronger in the 10.3 micron imagery (bottom left), and on the Daytime Convection RGB (bottom right) by evidence of yellow (red +green) pixels. Inflow feeder bands, a flanking line, towering cumulus above an invigorating RFD or flanking towers, and above anvil cirrus plume are also observed in the Day Cloud Convection and Cloud Phase Distinction RGBs (top panels) indicative of the storms likely being severe. In fact, the ProbSevere v3 and v2 output both indicated a very high probability of severe weather occurring with these storms with values over 90% (purple colors).

ProbSevere V3 and Splitting Cells over Montana on 10 Jun 2021

Posted in ProbSevere on by Kevin Thiel.

Our team was assigned to the Glasgow, MT WFO on this day.  The area was primed for explosive convective development, with the “triple point” over the CWA.  The dryline, cold front, and warm front were all apparent in radar imagery prior to convective initiation.

Radar reflectivity from KGGW from 1833-1920 UTC 10 Jun 2021. Note how the boundaries are readily apparent with the radar still in Clear-Air mode.

Although the main “action” fired east of the dryline, in NE Montana and eventually NW North Dakota (see SPC Storm Reports), a few robust storms also developed in the highly-sheared environment over the SE corner of the Great Falls, MT CWA. 

1200 UTC sounding from Great Falls, MT (KTFX). Note the steep lapse rates aloft and particularly the 67 knots of Surface-6 km shear.

A splitting cell was noted in radar imagery from KBLX (Billings, MT).  There was an mPing report of one-inch hail with this cluster of storms.

Radar reflectivity loop from KBLX from 2105-2133 UTC 10 Jun 2021. The split can clearly be seen by 2115 UTC.
MRMS Reflectivity At Lowest Altitude and ProbSevere3 time-series for the left-splitting (left) and right-splitting (right) storms. Within a couple of minutes of the split, ProbSevere3 correctly predicted that the right storm would become dominant and generally maintain its intensity. Meanwhile, the left-splitter would quickly weaken.

Suppose you were thrown into radar duties without time for a full-on environmental analysis.  In an environment conducive to splitting cells, ProbSevere3 can quickly provide guidance allowing the warning forecaster to anticipate which cell will become dominant.

– Professor Frink

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