GLM Lightning Preset 4-Panels

GLM lightning data provides very useful information to the operational forecaster, especially when properly combined with radar/satellite imagery. Would it be possible to take best practices suggestions from frequent users to lead to the creation of some pre-set 4-panel procedures that could be found in the AWIPS GLM data section (similar to what is available with radar base date, etc.)?

Sample 4-panel image pulled from the GLM Quicklook Guide

– Guillermo

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ProbSevere and GLM with supercell moving offshore the South Carolina coast

A thunderstorm located east of Charleston appeared to have some supercell characteristics as it moved south-southeastward towards the coast, with a kidney bean shape in reflectivity and a weak mid-level mesocyclone, as well as some deviant motion from the northwesterly flow. As it was over land it appeared to be strong but sub-severe, and maintained generally consistent 20 to 35 percent ProbSevere in v3. ProbSevere v3 seemed more consistent overall, with v2 jumping up and down more often, dropping down into the single digits at times. ProbSevere v3 did jump down below 20 percent briefly when GLM FED really dropped down. But the consistent lower-end probabilities at least indicated that this was a storm to be watched relative to the lower v2, and this may have at least allowed lead time on a low-end special marine warning before it moved offshore and strengthened.

The timeseries is somewhat useful if you just have one storm to look at, but with multiple storms I would probably just look at the loop in the ProbSevere plan view instead.

After it moved offshore, GLM FED increased, slightly in advance of a jump in MESH and associated jump in ProbSevere v3. ProbSevere v2 jumped ahead of v3 in probabilities as often occurs, though at that time MESH around 0.9 inches may have warranted the more conservative ~50-60% v3 approach. Later MESH jumped up to around 1.3 inches, and ProbSevere v3 jumped above 70 percent at this time as well.

Clockwise from top left: MRMS 18dbz echo top, MESH, reflectivity/ProbSevere/low-level azimuthal shear at 2130z.
Clockwise from top left: GLM FED, minimum flash area, reflectivity/ProbSevere, total optical energy at 2130z.

– Barry Allen

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ProbSevere in Jacksonville

The 0.5 degree SRM from JAX shows a concentrated area of wind within the cluster of storms in St. John County, FL with radar estimates of the wind near 50kts. Given the lightning jump illustrated by FED values quickly rising to ~170 flashes per 5 min, the storm is intensifying.

However, ProbSevere values are rather low with version 3 showing only 22% and version 2 showing 33%. ProbWind surprisingly was even lower with only 19%. This is a reflection of the lack of base radar data involved in the ProbSevere and ProbWind algorithms. Especially for ProbWind, base radar velocity data needs to be included in ProbWind for this product to be useful in identifying wind producing severe thunderstorms.

It would be useful to integrate base radar data from multiple single radars and combine these values into one algorithm. It may be useful to identify notable/sharp changes within velocity data between pixels which could help in picking out downdrafts.

– Fear the Shear

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Storms in northern and central Florida

GLM:

On the afternoon of June 15, 2 different convective regimes were noted across Florida, with different GLM lightning characteristics. A cold front was sinking southward towards the Florida panhandle, with convection developing along the Gulf sea breeze along the FL panhandle. Convection of more uncertain forcing developed in Central Florida.

Convection along the FL panhandle had higher MLCAPE and DCAPE due to mid-level drier air and steeper lapse rates, with somewhat lower PWATs. SBCAPE in excess of 5000 J/kg and MLCAPE in excess of 3000 J/kg was unusually high for this region. Convection in central FL was in a more tropical air mass, with PWATs at or above 2 inches and more saturated profiles. Convection in the FL panhandle developed in an area with very high microburst composite parameter values, indicating conditions very favorable for microbursts and localized damaging wind gusts.

12z TAE sounding:

15z XMR sounding:

MLCAPE 19z:

19z DCAPE:

19z PWATs:

Microburst composite parameter 19z:

The FL panhandle convection was more intense on radar and also had higher flash extent densities. It also tended to have lower minimum flash areas, centered on locally strong updrafts. Notable hail cores were observed aloft, and melting of these hailstones caused strong downdrafts and damaging wind reports, and in a few instances quarter size hail made it to the ground, with one instance of golf ball size hail..

1920z:

The central FL convection was weaker and had also been going on for longer, so there was some convective debris stratiform precipitation with larger minimum flash areas. Flash extent densities were lower than in the FL panhandle. There were still areas of lower minimum flash area centered on the updrafts.

The GLM flash points were very useful and lined up with the NLDN and ENTLN strikes and flashes. The parallax correction was especially useful for DSS purposes as partners often request notification on lightning strikes within a particular radius on the order of 8 to 20 miles, so an accurate location is important. At first glance there were much less flash points but this appeared to be due to the data only being 1 minute data without having the 5 minute accumulation that the NLDN and ENTLN offers. Having this similar 5 minute accumulation would be imperative for using the GLM flash points in operations. The sampled metadata for the flash points appeared less useful operationally. The flash area would be more of interest than the duration, but with a large number of flash points some sort of graphical depiction would be needed, and flash extent density seems to serve this purpose.

ProbSevere:

One interesting thing that was noted was v3 had much lower ProbHail than v2, while still having decent ProbSevere (mainly wind-driven values). We speculated that this was due to some of the machine learning based on environment and climatology, since severe hail would be less likely this time of the year with higher freezing levels/hot surface temperatures causing melting. However, in this case a golf ball size hail LSR was issued at 19:59z (report time appeared to be incorrect) for 2 ENE Saunders in Bay County, FL. This was comparable to MRMS MESH which maxed out at 1.89”.

On the technical side, I did want to note that typically I have sampling turned off in AWIPS, but then double-click on something that I want to sample. Since the ProbSevere timeseries plugin is also opened by double-clicking on the object, sometimes when I meant to double-click to sample the ProbSevere values I accidentally ended up opening a time series. And then I would double-click outside the ProbSevere area to sample something else or turn off sampling and I would get a black banner. Perhaps the timeseries doubleclick function could be turned on and off by making the ProbSevere product editable or not editable in the legend.

NUCAPS:

Gridded NUCAPS and individual NUCAPS soundings at 1840z showed steeper 700-500mb lapse rates than what was shown on the SPC mesoanalysis and some of the morning soundings, in areas away from convection. It’s hard to say which one was right, but the hail cores observed do seem more consistent with 700-500 mb lapse rates of near 7 C/km or greater. (Note that it would be useful to have contours to go with the images on the gridded NUCAPS plots.)

NOAA-20 sounding availability and example sounding (1823z)

1840z gridded NUCAPS 700-500mb lapse rate:

18z SPC mesoanalysis 700-500mb lapse rate:

NUCAPS also indicated the more saturated profiles/weaker lapse rates in the central FL convective regime.

NUCAPS did indicate some of the higher CAPE values, but with missing data in much of the area of interest as convection had already initiated when the pass occurred.

– Barry Allen

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

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

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

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

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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Utilizing GLM, NUCAPS, ProbSevere and Optical Winds Through the Stages From Convective Initiation to a Tornadic Supercell

A moderate risk of severe storms capable of producing large hail, damaging wind gusts and tornadoes occurred across the Dakotas. My focus was in the Bismarck, ND CWA where storms were likely initiating in eastern MT and then moving into the very unstable environment across western ND. All of the higher resolution models were a bit late on storm initiation as storms began to fire between 3-4 PM CT. The experiment began around 2 PM CT, which allowed for mesoanalysis of the pre-convective environment.

A NUCAPS CONUS NOAA-20 pass occurred at 19z across ND and then again at 20z where the eastern edge of this pass overlapped with the previous pass across western ND. At 19z, a comparison was made between the NUCAPS profile and a nearby RAP sounding at the same time. Below Image 1 shows the locations of the NUCAPS profile versus the RAP sounding. This area was chosen as it was close to where the satellite was showing some potential for convective initiation and was just east of the dryline in the area where the better instability was to be present.

Image 1a shows the location of the chosen 19z NUCAPS profile.
Image 1b shows the location of the chosen 19z RAP sounding.

Using sharppy the two profiles were then compared simultaneously. Both Images 2 and 3 show the two profiles, but image 2 will be highlighting the NUCAPS profile and associated instability values and image 3 will highlight the RAP sounding with associated instability parameters. Looking at the two profiles, there is not much difference in the mid to upper levels between the NUCAPS and RAP. However, the NUCAPS profile struggles more with the boundary layer features and temperature/dewpoint. Looking at observations, the current temperatures near that sounding location at 19z was 86 deg F with a dewpoint of 70 deg F. The RAP seemed to initialize these surface values pretty well and the thermodynamic profile east of the dryline, along with a bit of a capping inversion in place. Meanwhile, the NUCAPS profile struggled with the temperature and dewpoint, thus under doing the moisture and instability parameters. The CAPE values are noticeably different with the NUCAPS profile much lower with the instability due to these surface differences.

Image 2 shows the sharppy comparison of the 19z NUCAPS profile (colored) versus the RAP sounding (purple). The parameter values below are calculated based on the NUCAPS profile.
Image 3 shows the sharppy comparison of the 19z RAP sounding (colored) versus the NUCAPS profile (purple). The parameter values below are calculated based on the RAP sounding.

After seeing the discrepancies with the observed surface values versus the NUCAPS profile, I decided to grab the modified NUCAPS profile for the same location for comparison. Image 4 shows this modified sounding with a 10 degree difference between the non-modified surface temperature. The modified sounding shows a 82 deg F surface temperature, while the original NUCAPS profile had 91 deg F. With the cooler surface temperature the modified sounding showed a similar inversion to the RAP sounding between 750-800mb. The dewpoint temperature also was better representative of the actual surface dewpoint, which helped increase the instability parameters significantly. NUCAPS profiles tend to be a tad lower on the CAPE values, so the fact that the RAP is still about 1000 J/kg higher is not a surprise. However, with no RAOB sounding available and comparing the RAP with the modified NUCAPS profile there is quite a bit of similarity between the two in terms of the thermodynamic profile. Lastly, as storms begin to fire in the next hour or so and no RAOB profiles closeby, it might be useful to compare and utilize the temperature heights (0, -10, -20, and -30 deg C) for radar interrogation as storms initiate. Knowing the RAP and modified NUCAPS profiles were similar then the heights from the temperature levels could also be compared. The RAP does show higher heights than the modified NUCAPS profile, so this is something to keep in mind and monitor as storms fire along the dryline.

Image 4 shows the 19z modified NUCAPS sounding plotted with NSHARP.

Keeping with the theme of NUCAPS, there was another pass at 20z further west (as mentioned at the beginning) that overlapped the 19z pass in parts of western ND. This included the town of Bismarck, where the office put out a special 20z RAOB sounding. Bismarck was a bit further east than the previous sounding, but was still in the very favorable environment. Images 5 and 6 show the comparison between the NUCAPS sounding at 20z and the RAOB Bismarck special sounding at the same time. Similar results can be seen between the observed sounding and NUCAPS profile where the CAPE values are again lower in the satellite derived sounding. This time the NUCAPS profile did a much better job with the surface temperature and despite the temperature profile being a bit smoother due to lack of detail in the boundary layer, the profile was overall pretty similar to the RAOB temperature profile. The dewpoint profile on the NUCAPS was much drier at the surface and therefore had a bit of a drier boundary layer than the observed sounding, which is likely why the CAPE values are also a bit lower.

Image 5 shows the sharppy comparison of the 20z NUCAPS profile (colored) versus the Bismarck RAOB sounding (purple). The parameter values below are calculated based on the NUCAPS profile.
Image 6 shows the sharppy comparison of the 20z Bismarck RAOB sounding (colored) versus the NUCAPS profile (purple). The parameter values below are calculated based on the Bismarck RAOB sounding.

Once again the modified NUCAPS profile was compared (Image 7 below). The modified profile did a better job at showing the moisture in the boundary layer and attempted to pick up the dry layer at 650mb, which was actually at 700mb on the RAOB profile. Unfortunately, the temperature was too low and therefore the modified NUCAPS temperature profile shows a very sharp capping inversion that was unrealistic. Overall, the CAPE values did increase with the modified sounding versus the original NUCAPS profile and were closer to the observed sounding. Twice it has been noted that the heights of the temperature levels were closer between the non-modified NUCAPS profiles with the model/observed soundings. There may be some calculation in the modified sounding that is causing the heights to be lower and maybe unrealistic. In scenarios where there is a RAOB sounding, that is the best picture of the atmosphere you can get but it is great to compare the NUCAPS profiles for comparison to future events and potential trends in the satellite derived soundings.

Image 7 shows the 20z modified NUCAPS sounding plotted with NSHARP.

As storms began to initiate across eastern MT, both G16 and G17 GLM were utilized to look for lightning instances in the growing storms. Having both satellites can be super helpful, especially when one viewing angle may not see the strike, while the other does. This happened several times during storm initiation where one satellite would pick up a strike, while the other displayed nothing. Images 8-9 show this occurring twice in two different storms where each satellite picked up a strike that the other did not. As mentioned before, the viewing angle may not be in a good position for the satellite to see the storm’s top and therefore the strike is not bright enough to be detected. Along those lines, the scattering properties in the cloud are also not visible by the angle of the satellite’s view point and could cause the satellite to miss a strike. Lastly, there is a quality assurance that occurs for each product and if the strike wasn’t strong or long enough then the pixel could have been tossed out during this quality assurance. This is why it is so important to utilize both satellites when possible and it is a best practice to err on the side of whichever satellite is showing more lightning is probably more accurate.

Image 8 shows local radar and GLM flash points (top left), GLM minimum flash area and NLDN/GLD CG strokes (top right), GLM flash extent density and ENTLN CG/IC flashes (bottom left), and GLM total optical energy (bottom right). This image shows the G17 flash point and corresponding GLM gridded products, while G16 does not pick up on a flash point or any GLM lightning.
Image 9 shows local radar and GLM flash points (top left), GLM minimum flash area and NLDN/GLD CG strokes (top right), GLM flash extent density and ENTLN CG/IC flashes (bottom left), and GLM total optical energy (bottom right). This image shows the G16 flash point and corresponding GLM gridded products, while G17 does not pick up on a flash point or any GLM lightning.

ProbSevere version 2 and 3 were compared through the afternoon. The trend continued with version 2 remaining about 20-30% higher in all categories except the tornado probs. Version 3 has leaned towards being slightly higher than version 2 when it comes to tornado probabilities. ProbSevere time series was utilized to track the southernmost storm along the line of storms headed into western ND during the mid afternoon hours. Both radars were pretty far away on either side of the storms, with Glasgow’s radar being slightly closer. The lowest elevation scan was at around 13000-14000 feet when velocity began showing a strong mesocyclone. Image 10 shows the time series of ProbSevere and the readout comparing version 3 with version 2. All four ProbSevere categories were steadily increasing through the last hour with version 2 remaining higher than version 3. Version 2 shows close to 100% probabilities for all but tornado, making this storm look like a slam dunk due to the environmental parameters.  Meanwhile version 3 is slightly lower due to the fact that it can pick up on similar storms that occurred in a similar environment with little to no reports (from storm data). This is where version 3 adds in a bit more information to create more realistic probabilities.

Image 10 shows the ProbSevere readout for the tornadic storm in eastern MT, along with the time series showing steadily increasing probabilities of all threats. Note the lowest elevation scan with radar is at ~13500 feet.

Based on the strong rotation in Image 10, the tornado probabilities were close to 30 percent which is relatively high and should give a forecaster confidence on issuance with a lack of lower level radar scans. Chaser footage also helped to back the need for a tornado warning with images of wall clouds, funnels and more being reported from multiple sources. Image 11 shows the time series for ProbSevere along with multiple other parameters. One thing that was interesting to see was the tornado probability drastically dropped in version 2 but remained steady in version 3. Since version 2 is heavily using az shear, you can see the drop in MRMS az shear (red line on second plot down on the far left), which could be correlated with that probability drop in version 2. Also, the MLCIN is slowly increasing (blue line on second plot down on the far right) and could be playing a bit of a role in this drop as well. This is where version 3 might have a leg up on version 2 when it comes to tornado probabilities.

Image 11 shows the time series of version 2 and 3 of prob severe probabilities along with various other useful parameters.

Lastly, the optical winds were utilized to see the winds at the top of the storm. Image 12 shows the optical wind field for 200-100mb. You can see the cooler cloud tops in satellite below the wind field and then the associated diffluence aloft. This is an indication of the very strong supercell that is showing no signs of weakening anytime soon. Also, it is of note that there is another cool cloud top signature a bit further to the northwest associated with another strong supercell with diffluence aloft. The optical wind fields are useful in knowing what is going on aloft and the potential strengthening or even weakening of a storm.

Image 12 shows the 200-100mb layer of optical winds over the supercell in eastern MT.

– Harry Potter

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Comparing GLM Products from GOES 16 and 17- Wednesday

An approaching short wave trough as well as a remnant MCV moving through the area helped trigger thunderstorms over the upper Midwest.  Convection developed over Minnesota during the afternoon and evening hours.  Storms did not become severe near the Grand Forks, ND CWA until late in the afternoon. 

The upper Midwest is near the extent of coverage for both GOES 17 West and GOES 16 East.  This made it a good chance to compare how the GLM lightning products were affected by this issue.  Research has shown flash densities for both satellites diminish in this area, well away from the nadir of both satellites. 

Image 1 shows Flash Extent Density for GOES 17 on the left, and GOES 16 on the right.

The character and quality of the Flash Extent Density (FED) returns from each of the satellites can be seen, with GOES 17 showing a slightly westward tilt, and an eastward tilt in the returned grids for GOES 16.  The strongest storm in north central Minnesota has a higher and possibly better return on 17 than on 16.

Image 2 shows Minimum Flash Area for GOES 17 on the left, and GOES 16 on the right.

Values of Minimum Flash Areas from the satellites were quite different in some cases, and were also skewed as a result of the distance from the nadir of each satellite.  Placement of the flash areas also differed from “viewing” angle.

Image 3 shows Total Optical Energy from GOES 17 on the left, and GOES 16 on the right at 1958Z.

Total Optical Imagery (TOE) was also skewed.  It is interesting to note that the pixels of TOE in far southeastern ND change from minute to minute, as seen in Images 3 and 4.  At 1958Z, GOES 17 had an area of TOE returns along the ND/SD/MN borders, while GOES 16 had 2 separate areas, one in southern ND and one in west central MN.  By 1959Z, both GOES 17 and 16 agreed that there were 2 separate TOE returns in this region.

Image 4 shows Total Optical Energy from GOES 17 on the left, and GOES 16 on the right at 1959Z.

– Dana Scully

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