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Archive for the ‘Lightning Mapping Array’ Category

SPoRT is planning an assessment of Total Lightning products with several existing and new collaborators from WFOs, CWSUs, and National Centers, ranging in locations from southern Florida to New Mexico and Colorado.  From May 15 – July 15, 2014 operational forecasters will evaluate the application of total lightning to support severe storm, public safety, and aviation weather warning responsibilities.  To prepare, SPoRT is holding tele-training sessions with collaborators during the week of April 21 and has provided users several training modules as well as a Total Lightning Quick Guide.  These can be found via SPoRT’s Training Page and on the NOAA LMS.  Experience with total lightning data will prepare users for the GOES-R GLM as well as provide feedback from operations to researchers regarding the types of products users desire.

Total lightning (left) in a source density product form and radar reflectivity near the mixed phase level.  Higher values of total lightning correspond to regions where strong updrafts result in numerous particle collisions and charge separation.

Total lightning (left) in a source density product form and radar reflectivity near the mixed phase level. Higher values of total lightning correspond to regions where strong updrafts result in numerous particle collisions and charge separation. This image is from the NASA/SPoRT Quick Guide Training.

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The event in this blog post was provided by Amanda Terborg, satellite champion at the Aviation Weather Center.

SPoRT has been coordinating with the Aviation Weather Center (AWC) for a little over a year to incorporate the pseudo-geostationary lightning mapper (PGLM) mosaic demonstration product in operations, derived from ground-based lightning mapping arrays and part of the GOES-R Proving Ground.  This work culminated with the transition from demonstration mode to the AWC’s operations floor in September, thanks to Amanda’s coordination.  Shortly thereafter we received this particular event from October 7th.

On this day, one of the major items of interest was a line of storms moving through Washington D.C. and northern/western Virginia (Fig. 1).  The storms were not creating major disruptions as flights were able to remain ahead of the line or work their way behind the line of storms.  Figure 2 shows the aircraft tracks from 1402 UTC, which corresponds to the radar image in Fig. 1.  Due to the different projection types in N-AWIPs, the primary point of interest is circled in each image.  The major item of note is that there are no National Lightning Detection Network (NLDN) cloud-to-ground strike observations in the entire image.  However, the circled region shows a cluster of 3-4 flashes observed by the PGLM product.  As there are no corresponding NLDN strikes, these are solely intra-cloud flashes.  By observing the flight tracks, the aircraft were flying behind the main line of highest reflectivities.  Although the aircraft were behind the main line, Fig. 2 shows that approximately five aircraft flew into the region where the PGLM flashes were observed.  At around 1400 UTC one of those flights was struck by lightning.  The best news was that, while struck, the aircraft suffered no damage and continued safely on to its destination.

radar

Figure 1: The reflectivity (dBZ) observations from the Sterling, Virginia radar at 1402 UTC. The white circle indicates the region of interest.

PGLM

Figure 2: The corresponding pseudo-geostationary lightning mapper (PGLM) flash extent density product (filled boxes) and the Aircraft Situation to Display Industry (ASDI) flight tracks and heights (colored lines) at 1402 UTC. The white circle shows the same area of interest as that shown in Fig. 1. Not the observations of PGLM flashes and the lack of cloud-to-ground strike observations from the NLDN.

This example shows one of the major benefits of the future GOES-R Geostationary Lightning Mapper (GLM), as a space-borne instrument capable of observing total lightning (both intra-cloud and cloud-to-ground).  Radar is an excellent tool for helping develop safe flight tracks.  The ability of total lightning to observe intra-cloud flashes, as well as the spatial extent of these flashes, gives aviation planners additional information as to how to route aircraft, particularly in storms that have no cloud-to-ground observations.  This will be very important in data sparse regions were radar and total lightning are currently not available.

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REBLOGED from The GOES-R Proving Ground at the Aviation Weather Center (http://goesrawt.blogspot.com/2013/08/pglm-over-houston-center.html)

At the end of the day yesterday we saw several areas of convection begin to fire along a boundary into eastern TX and western LA. As it further developed it began to impede flight routes not only in the corridor between Dallas and Houston, but also between Houston and the eastern U.S. Figure 1 (Please click on the image to open the animation) shows the radar imagery from 1934 – 2036 Z overlaid with flight routes during that time. Note in particular the airspace between Dallas and Houston as the convection filled in.

rad_2Now check out the PGLM activity in the Houston network for the same time (Figure 2 – Please click on the image to open the animation).

Houston PGLMTowards the beginning of the loop the convective activity between Houston and Dallas was beginning to fill in but flights were still able to shoot the gaps without too much delay. However, the PGLM, while indicating densities of only 10/2 min or less, had flashes in or very near the routes of some of the aircraft. Then, as the convection further strengthened and the PGLM activity increased, air traffic began to divert completely around these areas instead of shooting the gaps.

In the case, you can see the potential utility of the GLM once GOES-R is launched, particularly in the earlier period of convective development. Radar echoes during that time didn’t look particularly intense within the gaps, however the PGLM was showing flashes.

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Last year, SPoRT had the opportunity to expand collaborations with the Aviation Weather Center (AWC) and Storm Prediction Center (SPC) through a GOES-R Visiting Scientist Proposal.  The effort was focused total lightning activities with the National Centers, who have different operational perspectives from a local forecast office.  In addition to providing training on total lightning, SPoRT learned a great deal about the day-to-day operations at each of these locations.  SPoRT works to put products into the end user’s decision support system.  At the National Centers, this is N-AWIPS, which presented an interesting challenge for the GOES-R Geostationary Lightning Mapper (GLM) demonstration data set, the pseudo-GLM.  Unlike a local forecast office, the National Centers needed to be able to see each network at the same time and this need resulted in the PGLM mosaic.  First transitioned in June 2012, the PGLM mosaic has been evaluated informally at AWC and SPC.

Next week, the PGLM will be a participant with the AWC’s Summer Experiment in support of the GOES-R Proving Ground.  In preparation, SPoRT has coordinated with the AWC and SPC GOES-R Satellite Champions to update the display with improved color curves, lightning mapping array range rings, and network status bars as well as producing a training module on the PGLM that is more geared towards the National Centers.  Below is a screen capture of the newest display in N-AWIPS.  SPoRT is currently coordinating with the GOES-R Satellite Champion to transition this product to the Weather Prediction Center / Ocean Prediction Center.  Lastly, generating the mosaic is possible through collaborations that provide the real-time data to SPoRT from several organizations.  There are currently seven collaborating networks.  These are the Colorado Lightning Mapping Array (Colorado State / New Mexico Tech), Houston Lightning Mapping Array (Texas A&M / New Mexico Tech), Langmuir Laboratory Lightning Mapping Array (New Mexico Tech), North Alabama Lightning Mapping Array (NASA), Oklahoma Lightning Mapping Array (University of Oklahoma), Washington D.C. Lightning Mapping Array (NASA), and West Texas Lightning Mapping Array (Texas Tech University).

new_pglm_mosaic2

A screen capture of the pseudo-GLM mosaic product in N-AWIPS for use at the National Centers with the newest color curves, range rings, and network status bars.

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Earlier this year, SPoRT in collaboration with the GOES-R Proving Ground, New Mexico Tech (developers of LMA technology), and Colorado State University (owner of the Colorado LMA), worked to gain access to the real-time data feed from the Colorado Lightning Mapping Arary.  In addition to helping the GOES-R Proving Ground, SPoRT is helping provide these data to WFOs Boulder and Cheyenne.  As we finalize these efforts the data have been displayed in a Google Earth web page, in addition to New Mexico Tech’s main page.  While observing the lightning in Colorado this afternoon, an interesting flash was observed around 1928 UTC.

First, here is a screen capture of the radar from WFO Boulder’s web page (Figure 1) at 1925 UTC.  We can see a strong cell (circled) southwest of Fort Collins, Colorado.  Of particular note is the low reflectivity values extending eastward towards Greeley, Colorado.

radar_reflectivity_1925_annotated

Figure 1: Radar reflectivity at 1925 UTC on 25 July 13 approximately 3 minutes before the long flash initiated.

Switching to the Colorado LMA source density display (Figure 2) at 1927 UTC, we can see some total lightning activity (~21-30 sources).  This is an electrically active storm, but is not undergoing a lightning jump that would indicate severe weather.  Let’s step ahead one more minute.

colma_25jul13_1927_annotated

Figure 3 shows the source densities again, but now for 1928 UTC.  Circled here is a single flash that originated from the storm southwest of Fort Collins, Colorado.  A rough estimate of the distance is ~25 miles.  This demonstrates an important lightning safety feature of total lightning.  These types of observations provide strong visual evidence that flashes are not always confined to the core of the storm.  This is very useful for educating individuals why you should stay indoors for 30 minutes after the last flash, even when the main body of the storm has passed.

colma_25jul13_1928_annotated

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It is great to have the LMA data still in operations at WFO Huntsville in our AWIPS II system.  Although thunderstorm activity has not been particularly severe this spring and early summer, the overall pattern has been sufficiently active to provide many instances where the LMA data have been useful.  Forecasters are employing it into their normal severe weather strategies once again, and such was the case this morning.  A couple of waves of thunderstorms moved across the Huntsville County Warning Forecast Area during the early morning hours, producing large amounts of lightning, small hail, and strong to damaging winds.  As thunderstorms passed through the Huntsville metro just after sunrise, they intensified, leading to severe thunderstorm warnings downstream in Jackson and DeKalb Counties in Alabama.  The warning forecaster, using the LMA data as a decision support aid noticed a “spike” in the source density values as storms were moving through the Huntsville metro and points just downstream.  The last spike was followed by increases in reflectivity values and wind speeds aloft, prompting the warning issuance.  While the LMA data alone did not provide sufficient evidence that a severe thunderstorm was occurring or was in the offing, it did enhance the forecaster’s awareness of the situation and served as supplementary evidence that the storm would potentially breach severe thresholds soon.

The first image below contains KHTX radar data and North Alabama LMA (lower left) from 1156 UTC this morning, June 27, 2013.

Image 1.

Image 1.  Data valid ~1156 UTC — from upper left, clockwise:  KHTX 8.7 degree reflectivity (dBZ), 8.7 degree velocity (kts), 8.7 degree Correlation Coefficient, North Alabama LMA (source density).

This elevated slice, at 8.7 degrees, represented a region of graupel and hail growth this morning, at about 21kft elevation AGL.  LMA data had indicated a few spikes earlier in the morning, while the storm was cycling in strength.  At 1156 UTC in the image above, you’ll notice that reflectivity values (upper left) were generally low, less than 50 dBZ.

A little later, LMA began to make some small jumps, over 200 sources by 1206 UTC (image 2).  Notice that reflectivities began to climb over 50 dBZ between the towns of Owens Crossroadas and Gurley.

Image 1.  Data valid ~1156 UTC -- from upper left, clockwise:  KHTX 8.7 degree reflectivity (dBZ), 8.7 degree velocity (kts), 8.7 degree Correlation Coefficient, North Alabama LMA (source density).

Image 1. Data valid ~1206 UTC — from upper left, clockwise: KHTX 8.7 degree reflectivity (dBZ), 8.7 degree velocity (kts), 8.7 degree Correlation Coefficient, North Alabama LMA (source density).

At 1216 UTC, a significant jump in LMA data occurred near the far eastern border of Madison County, near the town of Gurley, indicating the updraft was likely strengthening in the storm.  Source density values had climbed to about 400.  A corresponding increase in reflectivity values was ongoing, but increased further in the next series of radar scans.  Additionally, winds aloft began to increase (upper right), while a small area of relatively low CC values (lower right) appeared just northwest of Gurley.

Image 1.  Data valid ~1216 UTC -- from upper left, clockwise:  KHTX 8.7 degree reflectivity (dBZ), 8.7 degree velocity (kts), 8.7 degree Correlation Coefficient, North Alabama LMA (source density).

Image 1. Data valid ~1216 UTC — from upper left, clockwise: KHTX 8.7 degree reflectivity (dBZ), 8.7 degree velocity (kts), 8.7 degree Correlation Coefficient, North Alabama LMA (source density).

A little later, at 1241 UTC, a more significant increase in reflectivity occurred, with values climbing over 60 dBZ at the 8.7 degree elevation scan.  During the interim period, total lightning activity had decrased markedly, with values generally around or less than 100 sources in most updates.

Image 1.  Data valid ~1241 UTC -- from upper left, clockwise:  KHTX 8.7 degree reflectivity (dBZ), 8.7 degree velocity (kts), 8.7 degree Correlation Coefficient, North Alabama LMA (source density).

Image 1. Data valid ~1241 UTC — from upper left, clockwise: KHTX 8.7 degree reflectivity (dBZ), 8.7 degree velocity (kts), 8.7 degree Correlation Coefficient, North Alabama LMA (source density).

With velocity data at this level and lower levels indicating storm organization and low-mid level winds were increasing (not shown), increasing reflectivity and the recent spike in LMA, the decision was made to issue a severe thunderstorm warning, which was disseminated at  1247 UTC.

Image 1.  Data valid ~1251 UTC -- from upper left, clockwise:  KHTX 8.7 degree reflectivity (dBZ), 8.7 degree velocity (kts), 8.7 degree Correlation Coefficient, North Alabama LMA (source density).  Warning polygon issued at 1247 UTC overlaid in yellow.

Image 1. Data valid ~1251 UTC — from upper left, clockwise: KHTX 8.7 degree reflectivity (dBZ), 8.7 degree velocity (kts), 8.7 degree Correlation Coefficient, North Alabama LMA (source density). Warning polygon issued at 1247 UTC overlaid in yellow.

The thunderstorm did eventually produce wind damage in the Fyffe and Powell communities further downstream around 1225-1330 UTC (the warning was extended into those areas later).

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WFO Huntsville meteorologists were on-site at an outdoor concert in Cullman, Alabama, this past weekend to provide on-site decision support to local emergency managers, first responders, and concert organizers. In this environment, the focus shifts from watching for severe thunderstorms to watching for ANY thunderstorms, as even weak storms can be hazardous to crowds with minimal shelter.

View of Heritage Park in Cullman from the NWS desk

View of Heritage Park in Cullman from the NWS desk

The change in environment can be a challenge for meteorologists used to using the integrated & streamlined AWIPS system–while a “field” version of AWIPS is available, often most meteorologists have to rely on all web-based weather data.  Fortunately, it was easy to integrate SPoRT data into the DSS process via the SPoRT website–specifically total lightning from the North Alabama Lightning Mapping Array, and GOES-R Convective Initiation.  GOES-R CI data are useful for anticipating convective development and potentially improving lead time (needed for moving concertgoers to shelter).

NALMA data (provided via a Google Earth web interface) are linked more directly to public safety.  While radar can indicate heavy downpours, hail, and potentially gusty winds, it does not directly indicate where lightning is occurring.  NWS forecasters may be accustomed to using National Lightning Detection Network (NLDN) cloud-to-ground point data, but it is not available in the field in the same format.  Furthermore, total lightning data from the NALMA also provides a better idea of the spatial extent of lightning, and has sometimes shown an ability to provide some lead-time for cloud-to-ground strikes.  So NALMA data are of great interest to meteorologists providing decision support in the field.

NWS laptop with North Alabama Lightning Mapping Array data in the browser

NWS laptop with North Alabama Lightning Mapping Array data in the browser

Fortunately, concert organizers picked the two quietest weather days in June to hold their festivities!  There was little convective activity, and concertgoers were able to enjoy the music without giving thunderstorms a second thought.  But NWS meteorologists were well-prepared if hazardous weather would have threatened.

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So, when are total lightning data useful?  Well, there are many such cases, and we’ve described many of those in this blog…including my post yesterday.  But, they’re also particularly useful when the National Lightning Detection Network (NLDN) data drop out of AWIPS.  That is what happened earlier this evening, in an apparent system-wide outage that lasted for a couple of hours.  When you’re in operations, data redundancies are great to have, particularly for these types of cases.

At about 2247 UTC, a thunderstorm was moving across northern portions of Morgan County, AL, and was approaching southern Madison County (image 1).  Initially, the thunderstorm was expected to remain to the south and east of the Huntsville International Airport, for which we provide Airport Weather Warnings.

Image 1.  KHTX radar reflectivity (dBZ), overlaid with North Alabama LMA.

Image 1. KHTX radar reflectivity (dBZ, 2247 UTC), overlaid with North Alabama LMA source densities (2246 UTC).  The location of the Huntsville airport (KHSV) and a 5-mile radius ring (blue circle) from the KHSV location are also included.

However, by 2252 UTC, a small shower had developed along outflow to the northwest of the thunderstorm, and had just become electrically active (image 2).  Notice the (albeit small) LMA source density values just to the southwest of the airport radius ring at this time.  Of course, due to the NLDN data outage, we had no idea if the thunderstorm was producing CG strikes, but the total lightning data was sufficient for letting us know that the cell had become electrically active.

Image 2. KHTX radar reflectivity (dBZ, ), overlaid with North Alabama LMA source densities (.  The location of the Huntsville airport (KHSV) and a 5-mile radius ring (blue circle) from the KHSV ASOS location are also included.

Image 2. KHTX radar reflectivity (dBZ, 2252 UTC ), overlaid with North Alabama LMA source densities (2252 UTC). The location of the Huntsville airport (KHSV) and a 5-mile radius ring (blue circle) from the KHSV location are also included.

Armed with this new information, the forecaster issued an Airport Weather Warning for the Huntsville Airport at 2252 UTC.  The next image (image 3) shows that the LMA indicated lightning (at least intra-cloud) within the 5-mile radius ring at 2314 UTC.

Image 3. KHTX radar reflectivity (dBZ), overlaid with North Alabama LMA.  The location of the Huntsville airport (KHSV) and a 5-mile radius ring (blue circle) from the KHSV ASOS location can also be seen.

Image 3. KHTX radar reflectivity (dBZ, 2312 UTC), overlaid with North Alabama LMA source densities (2314 UTC). The location of the Huntsville airport (KHSV) and a 5-mile radius ring (blue circle) from the KHSV location are also included.

Knowing that intra-cloud flashes often precede CG strikes, and that thunderstorms in this type of environment will often eventually produce CG flashes, the total lightning data are invaluable, and can help to buy extra minutes of lead time in a rapidly evolving situation.  In this case however, we also see the added benefit when other data are simply unavailable.

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The North Alabama Lightning Mapping Array (NALMA) data have been in and out of operations at WFO Huntsville, AL for a while now, due mainly to AWIPS II testing and related issues.   After being unavailable in operations for about a week, we were able to get the data back into operations on the afternoon of Thursday, June 13th…and it couldn’t have happened at a better time.  I was working the Aviation Forecast desk and was assisting in monitoring radar for severe weather operations and the data were of great benefit once again.  The first image below shows a small cluster of thunderstorm cells moving southward from Tennessee across the border into Lauderdale County, Alabama…the very northwest corner of the state, at about 2000 UTC, although the various data in the image range from 1955 to 2000 UTC.  NALMA data overlay the radar data and were being used to monitor for lightning activity in the cells.  Notice that at this time, NALMA data indicated the cell near St. Joseph, Tennessee was electrically active (white-pinkish shading).  Also, notice that the cell to the west and just north of Threet, Alabama was not electrically active yet, according to both the NALMA and NLDN data.

Image 1.  KHTX radar data at 1955Z June 13, 2013...together with 15-min and 5-min NLDN data, NALMA source densities, and METAR observations valid at ~2000Z.

Image 1. KHTX radar data at 1955 UTC June 13, 2013…together with 15-min (2000 UTC) and 5-min (1955 UTC) NLDN data, NALMA source densities (1956 UTC), and METAR observations (~2000 UTC).

A little later, at about 2005 UTC, the cell had moved into Lauderdale County, now a few miles east of the town of Threet, and the NALMA indicated a sudden burst of electrical activity.  At this time, NLDN were not indicating any cloud-to-ground (CG) strikes.  Perhaps more importantly, this developing thunderstorm was moving towards the Muscle Shoals airport, which is located at the observation site (KMSL) in the northeastern section of Colbert County, directly to the south.

Image 2.

Image 2.  KHTX radar data at 2004 UTC June 13, 2013…together with 15-min (2000 UTC) and 5-min (2005 UTC) NLDN data, NALMA source densities (2004 UTC), and METAR observations (~2000 UTC).

The next image (Image 3), valid at about 2015 UTC shows the subsequent CG strikes in the NLDN data (horizontal blue lines).  Given the albeit small, but steady lightning production in this storm and increasing confidence that lightning was possible within 5 miles of the KMSL airport, a lightning warning was issued at 2015 UTC.

KHTX radar data at 1955 UTC June 13, 2013...together with 15-min and 5-min NLDN data, NALMA source densities, and METAR observations valid at ~2000 UTC.

Image 3.  KHTX radar data at 2014 UTC June 13, 2013…together with 15-min and 5-min NLDN data (2015 UTC), NALMA source densities (2014 UTC), and METAR observations (~2000 UTC).

The next image shows a CG strike within 5 miles of the KMSL airport at 2025 UTC, as noted by the small blue horizontal line north of KMSL and east of Florence.

KHTX radar data at 1955 UTC June 13, 2013...together with 15-min and 5-min NLDN data, NALMA source densities, and METAR observations valid at ~2000 UTC.

Image 4.  KHTX radar data at 2024 UTC June 13, 2013…together with 5-min NLDN data (2025 UTC), and METAR observations (~2000 UTC).

In this case, the LMA data alerted me that the cluster of cells had become electrically active, allowing me to shift my focus on when they might enter a 5-mile radius of the KMSL airport.   With a continuation of electrical activity as observed in the LMA data, my confidence was raised sufficiently, and the warning was issued for the airport.  The LMA data can be a great tool in situations like this, letting a forecaster know when a storm is electrically active and helping him/her to shift situational awareness appropriately, especially when CGs may not be initially present.  The LMA proved to be very beneficial in this case, allowing for some extra lead time with the airport weather warning for this cell.

Interestingly, the cell that entered eastern Lauderdale County was producing intra-cloud lightning throughout this time, but no CGs were reported by the NLDN.  Nevetheless, a forecaster would want some confirmation that a thunderstorm is in progress, particularly if he/she was involved in real-time weather watches for outdoor events, or for the possibility of lighting that could affect airport operations, as in the example above.

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This particular blog post focuses on total lightning observations from the Moore, Oklahoma tornado.  SPoRT is participating in the annual NOAA Hazardous Weather Testbed Spring Experiment in Norman, Oklahoma.  The Spring Experiment is demonstrating new NOAA and NASA experimental capabilities as part of the annual Experimental Warning Program.  One NASA capability being demonstrated is total lightning associated with severe / tornado weather events.  The data used were NOT from NASA, but from the Oklahoma Lightning Mapping Array operated by the University of Oklahoma.  NASA SPoRT has access to these data through a collaboration to support the Hazardous Weather Testbed and demonstrates SPoRT’s software plug-in to display these data in the National Weather Service’s AWIPS II system.  Also, this collaboration is demonstrating the SPoRT / MDL total lightning tracking tool.  This particular post discusses the connection of total lightning and tornado occurrence consistent with the “lightning jump” concept developed by Christopher Schultz (NASA Coop) and the lightning team here at the Earth Science Office.  These experimental data were not available to the Norman, Oklahoma forecast office and this post is intended as a discussion of how these data may have been used.

Figure 1 takes place at 1910 UTC and shows a 4-panel display from AWIPS II.  The lower two panels show radar observations of storm relative velocity (left) and reflectivity (right).  The top panels show two total lightning products.  The first is the source density product (left), which is used by several SPoRT partners in operations.  The pseudo-geostationary lightning mapper (PGLM – right) is the demonstration product SPoRT is providing to the Hazardous Weather Testbed this year to demonstrate what the future Geostationary Lightning Mapper observations may look like.  The PGLM data are derived from the ground-based lightning mapping array data.  In this case it is from the Oklahoma network provided to SPoRT with this collaboration.  Lastly, please note the two pop-up windows.  These display the output from the SPoRT / MDL total lightning tracking tool, which is a time series of the source densities (left) and PGLM (right) observations, respectively.  Newcastle and Moore, Oklahoma are circled for reference.

Figure 1: AWIPS II four panel display from 1910 UTC that shows the total lightning source density (upper left), and pseudo geostationary lightning mapper flash extent density (PGLM - upper right), along with the radar storm relative velocity (lower left), and radar reflectivity (lower right).  The pop-up windows show the total lightning tracking tool's time series plot for the source densities (left) and PGLM flash extent density (right), respectively.

Figure 1: AWIPS II four panel display from 1910 UTC that shows the total lightning source density (upper left), and pseudo geostationary lightning mapper flash extent density (PGLM – upper right), along with the radar storm relative velocity (lower left), and radar reflectivity (lower right). The pop-up windows show the total lightning tracking tool’s time series plot for the source densities (left) and PGLM flash extent density (right), respectively.

Both the source density and PGLM demonstrate a lightning jump around 1910 UTC, as shown by the spike in observations in the time series (~800 sources and 46 flashes, respectively).  Christopher Schultz’s official lighting jump algorithm supports this visual inspection as it too indicated a lightning jump.  Interestingly, the first severe thunderstorm warning was issued at 1912 UTC and based on radar observations at 1908 UTC.  Normally, we train that lightning jumps will precede severe weather, so why is the jump coincident with the initial severe thunderstorm warning?  The answer is that the environment in central Oklahoma was extremely favorable for tornadic supercells.  As such, as storms showed any signs of growth a warning was issued.  This is similar to how the Huntsville forecast office operated during the April 27, 2011 outbreak as there were so many violent storms across the region.  Given the environment, the total lightning would play a reinforcing role as the lightning jump at 1910 UTC indicates that this storm is rapidly strengthening and becomes rooted in the boundary layer.  One feature that the total lightning observations provide is a very rapid update cycle.  The total lightning data update every minute, versus the radar updating every 4-6 minutes.  This means that the total lightning observations are providing continuous updates into how the storm is evolving, allowing the forecaster to evaluate the storm’s growth in between radar volume scans.

We will next step forward to 1928 UTC, shown in Figure 2.

This is the same as Figure 1, but at 1928 UTC.

Figure 2: This is the same as Figure 1, but at 1928 UTC.

The total lightning observations begin to undergo a second, reinforcing lightning jump at 1928 UTC.  The time series plot is less obvious than from 1910 UTC, particularly with the source densities, but the lightning jump algorithm did flag a reinforcing jump at this time.  At this point, this is 12 minutes before the official tornado warning at 1940 UTC and 28 minutes prior to the reported touchdown time of 1956 UTC, near Newcastle, Oklahoma.  This reinforcing jump emphasizes to the forecaster that something is occurring and that the storm continues to intensify.  Given that a severe thunderstorm warning is already active, this reinforcing jump alerts the forecaster that this storm is unlikely to weaken soon.  The radar reflectivity emphasizes this as well, as it begins to take on a supercell structure and a faint hook echo may be forming (circled in reflectivity frame).

Figure 3 comes at 1940 UTC, shown in Figure 3, when the tornado warning was issued.

This is the same as Figure 1, but at 1940 UTC.

Figure 3: This is the same as Figure 1, but at 1940 UTC.

At this stage, the lightning activity has decreased somewhat after the initial jump at 1910 UTC and the reinforcing jump at 1928 UTC.  Radar continues to show intensification, particularly with the radar velocity couplet clearly evident to the west-southwest of Newcastle, Oklahoma.

We will next step ahead to 1950 UTC, just prior to the touchdown of the tornado at 1956 UTC in Figure 4.

Figure 4: This is the same as Figure 1, but at 1950 UTC.

Figure 4: This is the same as Figure 1, but at 1950 UTC.

At this stage, the tornado warning has been active for 10 minutes and the radar observations show the classic hook echo and velocity couplet signatures.  Both total lightning products show one final increase in activity, but given the high values for the past few minutes, this is not a third lightning jump.  The tornado would touchdown 6 minutes later just outside of Newcastle, Oklahoma before further intensifying and moving through Moore, Oklahoma.

Christopher Schultz provided an additional radar analysis that is a cross section of the radar azimuthal shear (a measure of the storm’s rotation) in time in Figure 5.  Red vertical bars show the occurrence of the original and reinforcing lightning jump at 1910 and 1928 UTC, respectively.  Of note is the large increase in azimuthal shear after each lightning jump prior to the tornado’s touchdown.

Figure 5: A radar azimuthal shear cross section plot from 1900-2300 UTC.  The red bars indicate the times of lightning jumps from the lightning jump algorithm.

Figure 5: A radar azimuthal shear cross section plot from 1900-2300 UTC. The red bars indicate the times of lightning jumps from the lightning jump algorithm.

Once again, I would like to re-iterate that these experimental data were not available to the forecasters in real-time and that this is a post-event analysis.  Overall, the total lightning data behaved as expected, with two lightning jumps preceding the severe weather and the tornado that would later impact Moore, Oklahoma.  Based on the extremely favorable environment for tornadic supercells, the total lightning data would play a supporting role providing insight into the storm’s development for a forecaster, particularly with its one minute update times.  Total lightning typically has more utility in marginal events, but the post-analysis here shows that the underlying concepts of what drives a lightning jump are just as valid here.

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