Lightning Mapping Array (LMA)
The SPoRT program works with three total lightning networks. These include the Lightning Mapping Arrays in North Alabama and Washington, D.C. as well as the Lightning Detection and Ranging Network at the Kennedy Space Center. Each card represents one of these networks. A green card marked as "Evaluation Product," is being used by at least one National Weather Service Forecast Office. Blue cards, marked "Research," exist for academic purposes and research. Real-time data are available by following the link at the bottom right of the card. The Overview section below describes the North Alabama network, but the basic concepts are applicable to each total lightning network.
Figure 1: The location of the 11 North Alabama Lightning Mapping
Array sensors (green dots and blue dot) and communications relays
(open green circles) across north Alabama.
The North Alabama Lightning Mapping Array (NALMA) was first activated in 2001 and officially transitioned to the Huntsville, Alabama National Weather Service Office in early 2003. Since the initial transition, SPoRT has successfully transitioned NALMA data to three other partner forecast offices. These include the Birmingham, Alabama as well as Morristown and Nashville, Tennessee Weather Forecast Offices. In addition, SPoRT has worked collaboratively with the lightning group here at the National Space Science and Technology Center (NSSTC) in Huntsville, Alabama to provide near real-time total lightning data to partner forecast offices in Melbourne, Florida and Sterling, Virginia using networks located in those regions. Sterling uses the Washington D.C. Lightning Mapping Array (DCLMA) while Melbourne receives data from the Kennedy Space Center Lightning Detection and Ranging Network (LDAR). Both of these networks are functionally similar to the NALMA network and forecast applications developed for one network can be used with another.
Figure 2. A comparison between what a cloud-to-ground
network observes in a lightning flash (left) versus what a total
lightning network will observe in a lightning flash (right).
Note how the cloud-to-ground network only provides a single
point of information. Also, the cloud-to-ground network
would observe nothing if the flash were solely intra-cloud.
The NALMA is a three-dimensional very high frequency (VHF) detection network of 11 VHF receivers deployed across northern Alabama with a base station and receiver located at the NSSTC (Figure 1). Solid green circles indicate a VHF receiver, while open green circles are wireless relay stations. The blue dot is the base station and 11th sensor located at the NSSTC. As of May 2009, two additional sensors located in Atlanta, Georgia have been added, in collaboration with researchers at Georgia Tech University. These are testing the effectiveness of the NALMA network using long baselines in the sensor placement.
Figure 3. A sample of 31 thunderstorms observed by the Kennedy Space
Center Lightning Detection and Ranging network showing the number of
cloud-to-ground strikes versus total lightning observed in each storm.
Notice how the intra-cloud component dominates the total lightning
observed in each storm. It is also interesting to note that two storms
had no cloud-to-ground strikes at all, yet were still very electrically active.
The NALMA system locates the sources of impulsive VHF radio signals from lightning by accurately measuring the time that the signals arrive at the different receiving stations. Each station records the magnitude and time of the peak lightning radiation signal in successive 80 microsecond intervals within a local unused television channel (channel 5, 76-82 MHz). Typically, hundreds of sources per flash can be reconstructed, which in turn produces accurate 3-dimensional lightning image maps (nominally <50 m error within a 150 km range). The sources can be thought of as the individual stepped leaders within a lightning flash. More detailed information can be found in Goodman et al. (2005). The primary advantage of NALMA, and the other total lightning networks, is that the networks detect total lightning, which is the combination of both cloud-to-ground and intra-cloud lightning. Figure 2 shows a rough comparison of what is detected between standard cloud-to-ground networks versus NALMA or any other lightning mapping array. The importance of detecting the intra-cloud flashes is that the intra-cloud flashes typically dominate the full number of flashes in a thunderstorm (Figure 3). With only cloud-to-ground data, forecasters are not receiving the full breadth of knowledge of how the storm is developing. Also, total lightning data are updated every 2 minutes, giving forecasters additional information about storm development in between radar volume scans.
Figure 4. A screen capture from AWIPS II showing the total lightning
flash extent density (colored contours) versus the cloud-to-ground
strike locations (negative and plus signs). Notice how the total
lightning indicates that lightning flashes are covering a wide area
whereas the cloud-to-ground observations only show single locations.
Operationally, total lightning data provide several advantages to forecasters. First, total lightning data often give a 3-5 minute lead time ahead of the first cloud-to-ground lightning strike. This improves lightning safety for the National Weather Service's Terminal Aerodrome Forecasts (TAFs) and Airport Weather Warnings (AWWs). This safety feature also can be used for incident support of special events. In addition, the total lightning data provides information about the spatial extent of lightning that is not available in the traditional cloud-to-ground data. Figure 4 shows the comparison of what is seen between a cloud-to-ground network observation and NALMA. Furthermore, the trend of total lightning in a thunderstorm can be used to provide advanced lead time on the development of severe weather. Forecasters often look for a lightning jump signature, where the total lightning observations rapidly increase in a short period of time. This lightning jump is indicative of a strengthening thunderstorm updraft. This insight into a storm's evolutionary development helps forecasters pinpoint which thunderstorms are intensifying or not. This provides a powerful tool in reducing the number of false alarms issued by the Weather Service as well as providing increased warning lead time. Figure 5 illustrates a lightning jump, both in a time series plot and with two screen captures from the National Weather Service's own decision support computer system. Additional information can be found at the SPoRT training page.
Figure 5. A time trend plot (top) of a storm that had two separate
lightning jumps at 1906 and 1920 UTC that led to the issuance of a
tornado warning at 1920 UTC ahead of the touchdown of an EF-1
tornado. The bottom two images show the AWIPS display before
(left) and during (right) the lightning jump.
SPoRT also utilizes the NALMA observations, and observations from other total lightning networks, as a risk reduction project for the GOES-R Geostationary Lightning Mapper (GLM) system set for launch later this decade. The GLM will be the first total lightning observation instrument in geostationary orbit and will provide total lightning observations over a massive domain, as opposed to the very small domains of the lightning mapping arrays. SPoRT uses the ground-based networks to help prepare for the GLM and its impacts on forecasting. More information can be found on SPoRT's GOES-R Proving Ground page.
Figure 6. The domain covered by the North Alabama Lightning Mapping Array.
For our end users, SPoRT provides a three dimensional total lightning data set that is updated every 2 minutes. Figure 6 shows that the NALMA network provides full coverage to the Huntsville and Nashville Weather Service county warning areas as well as partial coverage to Birmingham and Morristown offices. The grid has a horizontal extent of 460 x 460 km, with a 2 x 2 km grid resolution centered on the NSSTC. The vertical grid resolution is 1 km from 0-17 km. By providing NALMA data in AWIPS and AWIPS II, forecasters are able to interrogate the data on any of the 17 horizontal levels or examine the cumulative lightning density maps. The importance of using AWIPS / AWIPS II is that it puts the NALMA data into the forecasters' own decision support tool where they can readily compare the NALMA data to NEXRAD radar observations or any other available data sets to enhance situational awareness, particularly during severe weather events.
Forecasters predominantly use the cumulative lightning density map in real-time operations as opposed to any single vertical level due to forecasting time constraints. However, with the greater flexibility of AWIPS II, SPoRT is working with our partners to potentially include more of the available three dimensional observations.
References: Goodman, S. J., and Coauthors, 2005: The North Alabama Lightning Mapping Array: Recent severe storm observations and future prospects. Atmos. Res., 76, 423-437.