Highlighted Papers

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Goss, H. 2020:  Lightning research flashes forward, Eos, 101, Published on 24 April 2020.

A greater understanding of lightning mechanisms is spurring the development of more accurate weather forecasting, increased public health precautions, and a more sophisticated understanding of lightning itself.

Bruning, E., C. E. Tillier, S. F. Edgington, S. D. Rudlosky, J. Zajic, C. Gravelle, et al., 2019: Meteorological imagery for the geostationary lightning mapper. J. Geophy. Res: Atmos., 124, 14285– 14309. 

This paper describes a method for creating imagery from the Geostationary Lightning Mapper instrument on the new geostationary weather satellites launched by the United States. The imagery overlays directly on and can be animated like other weather satellite images, making it more suitable for diagnosing thunderstorm behavior than the simple lightning location plots easily made from the publicly available data. The imagery can be summed to create analyses of lightning on climate time scales. The imagery illustrates that extensive lightning discharges exist in some storm systems and that distant ground strike points are joined by a single extensive lightning channel in the cloud.

Cecil, D. J., D. E. Buechler, J. R. Mecikalski, and X. Li, 2020:  Rapid scan visible imagery from the Geostationary Lightning Mapper (GLM) at 2.5-minute intervals. Mon. Wea. Rev.

The GLM transmits background visible-band images of its field of view every 2.5 min. The background images (2.5-min sampling) can potentially fill temporal gaps between full-disk imagery from the GOES satellites’ Advanced Baseline Imager. This paper applies an initial calibration and geolocation of the GLM background images and focuses on animations for two cases: a volcanic eruption in Guatemala and a severe thunderstorm complex in Argentina. Despite coarse horizontal resolution, the rapid updates from GLM background images appear to be useful in these cases. The 3 June 2018 eruption of Fuego Volcano appears in the GLM background imagery as an initial darkening of the pixels very near the volcano and then an outward expansion of the dark ash cloud. .

Lyons, W.A., E.C. Bruning, T.A. Warner, D.R. MacGorman, S. Edgington, C. Tillier, and J. Mlynarczyk, 2020: Megaflashes: Just How Long Can a Lightning Discharge Get?. Bull. Amer. Meteor. Soc., 101, E73–E86. 

The new Geostationary Lightning Mapper (GLM) provides a tool suited to investigating mesoscale lightning. On 22 October 2017 at 0513 UTC, the GLM indicated a lightning discharge originated in northern Texas, propagated north-northeast across Oklahoma, fortuitously traversed the Oklahoma LMA (OKLMA), and finally terminated in southeastern Kansas. The NLDN reported 17 positive cloud-to-ground flashes (+CGs), 23 negative CGs (−CGs), and 37 intracloud flashes (ICs) associated with this massive discharge, including two +CGs capable of inducing sprites, with others triggering upward lightning from tall towers. Combining all available data confirms the megaflash, which illuminated 67,845 km2, was at least 500 km long, greatly exceeding the current official record flash length. Yet even these values are being superseded as GLM data are further explored, revealing that such vast discharges may not be all that uncommon.

Peterson, M. J., Lang, T. J., Bruning, E. C., Albrecht, R., Blakeslee, R. J., Lyons, W. A., et al. (2020). New World Meteorological Organization certified megaflash lightning extremes for flash distance (709 km) and duration (16.73 s) recorded from space. Geophy. Res. Let., 47, e2020GL088888.

Analysis of new satellite data has identified lightning extremes for horizontal distance (709 km) and greatest duration (16.730 s).

Rudlosky, S., S. Goodman, K. Calhoun, C. Schultz, A. Back, B. Kuligowski, S. Stevenson, and C. Gravelle, 2020:  Geostationary Lightning Mapper Value Assessment, NOAA Technical Report NESDIS 153. 

This value assessment documents societal and economic benefits that can be attributed to a Geostationary Lightning Mapper (GLM) to advise future satellite architecture decisions. The report examines the use-inspired science and public benefits of space-based lightning measurements that address NESDIS mission objectives for geostationary earth and extended orbit (GEO-XO) observations. We describe operational use cases to illustrate GLM value being realized through the actions of various decision makers, and identify well documented benefit pools where the GLM adds value.

Bateman, M., D. Mach, and M. Stock, 2020:  Further investigation into detection efficiency & false alarm rate for the Geostationary Lightning Mappers aboard GOES‐16 and GOES‐17. Earth and Space Science, 7, e2020EA001237.

In order to evaluate the quality of the GLM data, we need to compare it to other, well‐understood sources of lightning data. To account for the lack of high detection efficiency ground truth data over much of the viewing GLM area, we have increased the time window for comparisons to ± 10 min. Using the larger time window, we find that the GLMs see as much as 90% of the lightning seen by other lightning detecting systems.

Rutledge, S. A., K. A. Hilburn, A. Clayton, B. Fuchs, and S. D. Miller, 2020: Evaluating Geostationary Lightning Mapper flash rates within intense convective storms. J. Geophy. Res. Atmos., 125, e2020JD032827.

We evaluate GLM detection efficiency (DE) for a special class of convective storms characterized by anomalous charge structures. Anomalous storms are characterized by extreme flash rates, low median flash heights, and intense precipitation. This study contrasts two regions: Colorado, where electrically “anomalous” storms are numerous, and Alabama, where they are rare. The GLM DE is found to vary with the geometric size of the flash and with cloud water path, the latter depending on flash height and cloud water content. Optical scattering (attenuation) by precipitation‐sized particles does not appear to be a factor since precipitation particles contain much less surface area than cloud particles. The size of the flash is correlated with its optical brightness, and the cloud water path is correlated with optical extinction. 

Schultz, C. J., V. P. Andrews, K. D. Genareau, and A. R. Naeger, 2020: Observations of lightning in relation to transitions in volcanic activity during the 3 June 2018 Fuego Eruption. Sci Rep, 10, 18015. 

Satellite and ground-based remote sensing are combined to characterize lightning occurrence during the 3 June 2018 Volcán de Fuego eruption in Guatemala. The combination of the space-based Geostationary Lightning Mapper (GLM) and ground-based Earth Networks Total Lightning Network observed two distinct periods of lightning during this eruption totaling 75 unique lightning flash occurrences over five hours (57 in cloud, 18 cloud-to-ground). The first period of lightning coincided with the rapid growth of the ash cloud, while the second maxima occurred near the time of a deadly pyroclastic density current (PDC) and thunderstorm. Ninety-one percent of the lightning during the event was observed by only one of the lightning sensors, thus showing the importance of combining lightning datasets across multiple frequencies to characterize electrical activity in volcanic eruptions. 

Kong, R., M. Xue, A.O. Fierro, Y. Jung, C. Liu, E.R. Mansell, and D.R. MacGorman, 2020: Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI EnKF for the Analysis and Short-Term Forecast of a Mesoscale Convective System. Mon. Wea. Rev., 148, 2111–2133.

This study assimilates, for the first time, real GLM total lightning data in an ensemble Kalman filter (EnKF) framework. The lightning flash extent density (FED) products at 10-km pixel resolution are assimilated. FED observation operators based on graupel mass or graupel volume are used. The assimilation of FED is primarily effective in regions of deep moist convection, which helps improve short-term forecasts of convective threats, including heavy precipitation and lightning. Direct adjustments to graupel mass via observation operator as well as adjustments to other model state variables through flow-dependent ensemble cross covariance within EnKF are shown to work together to generate model-consistent analyses and overall improved forecasts.

Thiel, K. C., Calhoun, K. M., Reinhart, A. E., & MacGorman, D. R. (2020). GLM and ABI characteristics of severe and convective storms. J. Geophy. Res. Atmos., 125, e2020JD032858.

This study investigates the utility of lightning flash data from the new Geostationary Lightning Mapper (GLM) on the recently launched U.S. weather satellites. Guidance regarding the use of GLM data is needed to improve the quality of forecasts and research, especially when using the data for nonsevere and severe thunderstorms. Comparisons are made between the rate of flashes and their size, along with cloud‐top properties from another instrument on the weather satellite, the Advanced Baseline Imager (ABI). Using 7 weeks of data during the peak of the 2019 severe storms season (April and May), we demonstrate that higher lightning flash rates are correlated with smaller‐sized flashes as a thunderstorm's cloud top becomes higher and colder. Cloud tops colder than approximately −30°C may also be used to discriminate between regions with and without lightning activity.

Zhang, D., and K. L. Cummins, 2020: Time evolution of satellite‐based optical properties in lightning flashes, and its impact on GLM flash detection. J. Geophy. Res: Atmos., 125. 

During 2017–2018, GLM detected more than 70% of all lightning flashes in central Florida. The GLM‐detected flashes typically last longer and occupy larger areas. Data from the Lightning Imaging Sensor (LIS) and modeling results indicate that longer‐duration flashes tend to produce brighter and larger light sources for GLM to detect, whereas shorter‐duration flashes tend to produce dimmer and smaller light sources that the GLM might not detect. This finding furthers our understanding of the underlying GLM detection behaviors and will help improve how GLM products are used in severe weather forecasting and other applications.


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