GOES-R geostationary lighTninG mapper Applications to Improve Tornado Forecasting

Amber Liggett and Ed Oswald, millersville university meteorology

Video Credit: NASA Goddard Multimedia

While GOES-R promises to be a huge step forward in remote sensing for meteorologists and oceanographers alike, the features of NOAA's next-generation satellite go far beyond just imaging. One of the tools on-board GOES-R is the Geostationary Lightning Mapper (GLM), the first lightning mapper in geostationary orbit that will provide scientists with near real-time data on lightning activity across the satellite's entire coverage area.

While the GLM will certainly aid in earlier detection of severe storms, one area where researchers hope to put the sensor to use is in the area of early tornado detection. Recent research suggests that heightened lightning activity may precede the development of tornadoes. With the assistance of GLM, scientists hope that warning lead times may be improved, potentially saving lives in the process.

LITERATURE REVIEW

Lightning, both natural and artificially-initiated, remains the primary weather hazard to spaceflight operations (Merceret et al. 2010). Scientists study lightning mapping data to learn how changes in lightning behavior can be associated with various types of storms. Lightning mapping has shown that some supercell thunderstorms have “lightning holes” where updrafts are located and precipitation is scarce, just before a storm becomes severe. This information could alert forecasters about developing severe conditions (NSSL 2016).

Concepts for the GLM have been explored since the early 1980s, culminating with the single telescope design having high detection efficiency for total lightning approaching 90% with near uniform storm-scale spatial resolution owing to the variable pitch pixel detector design (Goodman et al. 2013). Historically, small scale studies of the electrification of thunderstorms and the resulting lightning have been performed in an attempt to understand lightning’s physical principles (Christian et al. 1992). Others have measured electric fields, including The New Mexico Tech (NMT) with their GLM array which was developed in the mid-1990s.

Vaisala promotional video on on the National Lightning Detection Network (NLDN).

For example, arrays of instruments that solely examine the electrostatic component of radiated electric field include Kennedy Space Center and NMT, as well as single station fast antennas. In the past, arrays have been designed to measure all components of the radiated electric field. The Lightning Mapping Array (LMA) and the National Lightning Detection Network (NLDN) are beneficial for detecting lightning, though LMA cannot yield any energetic information and NLDN poorly measures ICs. So, GLM can further improve ground truth for space-based measurements by utilizing a newly developed ground based electric field change meter array (Christian and Gheno 2011).

Prior to GLM, ground based sensors were the primary detection method for cloud-to-ground and cloud-to-cloud lightning (NASA 2014). The GLM flight model was first scheduled for delivery in 2013 for integration onto the GOES-R spacecraft. This would have then led to a planned launch aboard an Atlas-V 541 rocket at the end of 2015, though it was successfully launched with GOES-R in 2016 (NASA 2016). The ground processing algorithms are an extension of the algorithms developed for the earlier OTD and LIS research instruments in low Earth orbit (Goodman et al. 2013).

The GLM represents the next step in the global observing system for continuous operational high fidelity measurements of lightning on Earth (Goodman et al. 2013). Its goal is to measure the energetics of lightning which is tied to the “net charge involved”. In order to achieve this goal, the electric field change due to a stroke/flash must first be measured. GLM missions include utilizing real-time lightning data to predict longer tornado warning times, storm cell tracking, and decadal lightning data (Christian and Gheno 2011). GOES-R is the stepping stone for the GLM as this machine is the first of its kind. Integration within GOES-R allows it to orbit North America (NASA 2014).

The GOES-R satellite with the major instruments identified. (NASA)

THE GLM

specifications

  • Staring CCD imager (1372x1300 pixels)
  • Near uniform spatial resolution: 8 km nadir, 14 km edge field of view
  • Coverage up to 52 degrees north latitude
  • 0-90% flash detection day and night
  • Single band 777.4 nm
  • 2 millisecond frame rate
  • 7.7 Mbps downlink data rate (for comparison- TRMM LIS 8 kbps)
  • 20 second product latency

in detail

The GLM is a near-infrared optical instrument that is capable of detecting momentary changes in brightness, which is how it's able to detect lightning flashes. The GLM operates at a resolution of 10 kilometers, and it is able to detect trends in lightning activity. These trends show promise in helping meteorologists gauge the severity of storms, as well as potentially increase warning times.

Scientists also plan to catalog the measurements of the GLM to monitor decadal changes in lightning activity. Since it is the first geostationarity lightning detector of its kind, it provides scientists with data that was previously unavailable.

The only similar large-scale lightning detector aboard a satellite was the Lightning Imaging Sensor (LIS) which was aboard the Tropical Rainfall Measuring Mission (TRMM) satellite, a joint project of NASA and the Japan Aerospace Exploration Agency (JAXA). That satellite was in operation from 1997 through 2015.

Total lightning measured by TRMM during 2012.

TRMM was not a geostationary satellite: its coverage was limited to between 35 degrees north and 35 degrees south latitude. The LIS could also only view a particular point on the surface for 80 seconds, which was just enough time to estimate a flashing rate, but not to do much else that would be of great benefit to forecasters. Thus, a geostationary lightning detector was something many researchers pushed for over the past three decades.

As early as the 1980s there were plans to put a predecessor called the Lightning Mapper Sensor on the previous generation of GOES satellites, but that never materialized. Plans for a modern version of the LMS were finalized as part of the preparations for the GOES-R generation of satellites during the 2000s.

But why is the GLM so important? Putting a lightning detection system in orbit has many advantages over the traditional ground-based system. Those traditional systems only work over land, coverage over water is only available close to shore, and only cloud-to-ground and ground-to-cloud lightning is detectable. A lightning mapper in orbit can also serve as a backup to monitor storm activity when radar is not available, either due to downtime or areas where radar has traditionally had poor coverage, and also capture cloud-to-cloud strikes as well.

Potential coverage area for the GLM once both GOES-East and West are replaced with GOES-R and S.

The GLM could also potentially assist hurricane forecasters in providing accurate measurements of the intensity of tropical cyclones. Like tornadic activity, studies have suggested an increase in lightning activity might precede the peak intensity of a tropical cyclone, and the GLM may provide further evidence of some type of link.

Of course, the GLM has its own set of disadvantages as well. The 10km resolution still is quite coarse, which partially explains the instrument's less than 100% detection rate.

GLM'S APPLICATION TO TORNADO FORECASTING

As early as the 1950s, atmospheric scientists were theorizing that there was some type of connection between lightning and tornadic development. Most notably, Oklahoma A&M Professor Herbert L. Jones theorized that tornadic storms emit much more high-frequency electrical energy versus non-tornadic ones (Jones 1952).

Jones' theories actually led to the development and retail sale of "tornado detectors," which looked for changes in the local electric field. However the concept was faulty, and these devices more a gimmick than an actual method of detection. But the concept of some causational link between electrical activity and lightning and tornadic activity did not go away.

Newer studies are again suggesting that link. Perhaps the impetus for much of the recent discussions surrounding this was the May 2013 Moore, Oklahoma EF5 tornado. Post-event analyses revealed that two distinct lightning "jumps" occurred about 19 minutes before the onset of hail, and 26 minutes before the tornado first touched down (Carey et al 2014).

AWIPS II display showing the initial and reinforcing lightning jumps at 1910 and 1928 UTC on May 21, 2013. Ahead of the tornado. The tornado touched down at 1956 UTC. (SPoRT)

This wasn't the first time researchers found a possible link. Shortly after the launch of the Optical Transient Detector in 1995, the instrument passed over a severe storm in Oklahoma on April 13. During the pass, the satellite measured a surge of lightning in a particular storm to more than 60 bolts per second. About a minute later, ground observers confirmed a tornado on the ground (Davidson 1996).

GLM will be a major source of evidence to either confirm or disprove the link between heightened lightning activity and tornadic risk. As mentioned earlier, ground systems only capture a portion of the actual lightning activity. If the key is in cloud-to-cloud strikes, there is little research to prove that link.

CONCLUSION

Lightning has the important role of maintaining an electrical balance between Earth, its atmosphere and potential changes in severe weather. The launch of GOES-R GLM is a stepping stone for analyzing near real-time data on lightning activity across the satellite's entire coverage area. This near-infrared optical instrument thoroughly examines the energetics of lightning, yielding early warning of ground strike hazards, and early tornado detection. With the great amounts of data collected, GLM will be able to assist severe storm detection and long-term climate variability studies.

works cited

Christian, H. J., and Coauthors, 1992: Lightning Imaging Sensor for the Earth Observing System. NASA Tech. Memo. NASA TM-4350, 44 pp.

Christian, H.J., and K. M. Gheno, 2011: GOES-R Geostationary Lightning Mapper. Accessed 9 December 2016. [Available online at http://www.goes-r.gov/downloads/2012-AMS/02/Gheno.pdf.]

Davidson, K, 1996: No Man's Land, Twister The Science of Tornadoes and the Making of a Natural Disaster Movie, Pocket Books, 175. Accessed 5 December 2016. [Available online at https://books.google.com/books?id=hRUxgckfjeoC&printsec=frontcover&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=false.]

Goodman, S. J., and Coauthors, 2013: The GOES-R Geostationary Lightning Mapper (GLM). Atmos. Res., 125–126, 34–49.

Jones, H. L., 1952: A Sferic Method of Tornado Tracking and Identification, Engineering Experiment Station [Oklahoma Agricultural and Mechanical College], 1-9. Accessed 7 December 2016. [Available online at https://books.google.com/books/about/A_Sferic_Method_of_Tornado_Tracking_and.html?id=_L5EGwAACAAJ.]

Merceret, F. J., and Coauthors, 2010: A History of the Lightning Launch Commit Criteria and the Lightning Advisory Panel for America’s Space Program. NASA/SP—2010–216283, 234 pp.

NASA, 2011: NASA Facts: TRMM Instruments Lightning Imaging Sensor. Accessed 5 December 2016. [Available online at https://trmm.gsfc.nasa.gov/overview_dir/lis.html.]

NASA, 2014: First-of-its-kind Geostationary Lightning Mapper Completed for GOES-R Satellite. Accessed 7 December 2016. [Available online at https://www.nasa.gov/content/goddard/geostationary-lightning-mapper-completed-for-goes-r-satellite/.]

NASA, 2016: NASA: GOES-R Geostationary Lightning Mapper. Accessed 8 December 2016. [Available online at http://www.goes-r.gov/spacesegment/glm.html].

NESDIS, 2016: GOES-R Geostationary Lightning Mapper (GLM). Accessed 9 December 2016. [Available online at http://www.goes-r.gov/education/docs/Factsheet_GLM.pdf.]

NSSL, 2016: NSSL Research Lightning. Accessed 9 December 2016. [Available online at http://www.nssl.noaa.gov/research/lightning/.]

Stano, G. J., 2013: Total Lightning Perspective of the Moore, Oklahoma Supercell. Accessed 7 December 2016. [Available online at https://nasasport.wordpress.com/2013/05/24/total-lightning-perspective-of-the-moore-oklahoma-supercell/.]

Stano, G.J., 2014: A Total Lightning Perspective of the 20 May 2013 Moore, Oklahoma Supercell. Accessed 7 December 2016. [Available online at https://ntrs.nasa.gov/search.jsp?R=20140007286.]

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