• Baker, M. B., and J. G. Dash, 1994: Mechanism of charge transfer between colliding ice particles. J. Geophys. Res., 99, 10 62110 626, https://doi.org/10.1029/93JD01633.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bateman, M. E., and D. M. Mach, 2020: Preliminary detection efficiency and false alarm rate assessment of the Geostationary Lightning Mapper on the GOES-16 satellite. J. Appl. Remote Sens., 14, 032406, https://doi.org/10.1117/1.JRS.14.032406.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Biagi, C. J., K. L. Cummins, K. E. Kehoe, and E. P. Krider, 2007: National Lightning Detection Network (NLDN) performance in southern Arizona, Texas, and Oklahoma in 2003–2004. J. Geophys. Res., 112, D05208, https://doi.org/10.1029/2006JD007341.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bruning, E. C., and D. R. MacGorman, 2013: Theory and observations of controls on lightning flash size spectra. J. Atmos. Sci., 70, 40124029, https://doi.org/10.1175/JAS-D-12-0289.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bruning, E. C., and Coauthors, 2019: Meteorological imagery for the Geostationary Lightning Mapper. J. Geophys. Res. Atmos., 124, 14 25814 309, https://doi.org/10.1029/2019JD030874.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Buck, T., A. Nag, and M. J. Murphy, 2014: Improved cloud-to-ground and intracloud lightning detection with the LS7002 Advanced Total lightning sensor. Proc. WMO Tech. Conf. on Meteorological and Environmental Instruments and Methods of Observation, Saint Petersburg, Russia, WMO, 8 pp., https://www.wmo.int/pages/prog/www/IMOP/publications/IOM-116_TECO-2014/Session%201/P1_9_Buck_TotalLightningSensor.pdf.

    • Search Google Scholar
    • Export Citation
  • Carey, L. D., M. J. Murphy, T. L. McCormick, and N. W. Demetriades, 2005: Lightning location relative to storm structure in a leading-line trailing stratiform mesoscale convective system. J. Geophys. Res., 110, D03105, https://doi.org/10.1029/2003JD004371.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Caylor, I. J., and V. Chandrasekar, 1996: Time-varying crystal orientation in thunderstorms observed with multiparameter radar. IEEE Trans. Geosci. Remote Sens., 34, 847858, https://doi.org/10.1109/36.508402.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cummins, K. L., and M. J. Murphy, 2009: An overview of lightning location systems: History, techniques, and data uses with an in-depth look at the U.S. NLDN. IEEE Trans. Electromagn. Compat., 51, 499518, https://doi.org/10.1109/TEMC.2009.2023450.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doviak, R. J., V. Bringi, A. Ryzhkov, A. Zahrai, and D. Zrnić, 2000: Considerations for polarimetric upgrades to operational WSR-88D radars. J. Atmos. Oceanic Technol., 17, 257278, https://doi.org/10.1175/1520-0426(2000)017<0257:CFPUTO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Elsenheimer, C. B., and C. M. Gravelle, 2019: Introducing lightning threat messaging using the GOES-16 day cloud phase distinction RGB composite. Wea. Forecasting, 34, 15871600, https://doi.org/10.1175/WAF-D-19-0049.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emersic, C., and C. P. R. Saunders, 2010: Further laboratory investigations into the relative diffusional growth rate theory of thunderstorm electrification. Atmos. Res., 98, 327340, https://doi.org/10.1016/j.atmosres.2010.07.011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fleenor, S. A., C. J. Biagi, K. L. Cummins, E. P. Krider, and X. M. Shao, 2009: Characteristics of cloud-to-ground lightning in warm-season thunderstorms in the Central Great Plains. Atmos. Res., 91, 333352, https://doi.org/10.1016/j.atmosres.2008.08.011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fuelberg, H. E., R. J. Walsh, and A. D. Preston, 2014: The extension of lightning flashes from thunderstorms near Cape Canaveral Florida. J. Geophs. Res. Atmos., 119, 99659979, https://doi.org/10.1002/2014JD022105.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giangrande, S. E., T. Toto, A. Bansemer, M. R. Kumjian, S. Mishra, and A. V. Ryzhkov, 2016: Insights into riming and aggregation processes as revealed by aircraft, radar, and disdrometer observations for a 27 April 2011 widespread precipitation event. J. Geophys. Res. Atmos., 121, 58465863, https://doi.org/10.1002/2015JD024537.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goodman, S. J., and Coauthors, 2013: The GOES-R Geostationary Lightning Mapper (GLM). Atmos. Res., 125–126, 3449, https://doi.org/10.1016/j.atmosres.2013.01.006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gremillion, M. S., and R. E. Orville, 1999: Thunderstorm characteristics of cloud-to-ground lightning at the Kennedy Space Center, Florida: A study of lightning initiation signatures as indicated by WSR-88D. Wea. Forecasting, 14, 640649, https://doi.org/10.1175/1520-0434(1999)014<0640:TCOCTG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Harkema, S., C. J. Schultz, E. B. Berndt, and P. M. Bitzer, 2019: Geostationary Lightning Mapper flash characteristics of electrified snowfall events. Wea. Forecasting, 34, 15711585, https://doi.org/10.1175/WAF-D-19-0082.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Heinselman, P. L., and A. V. Ryzhkov, 2006: Validation of polarimetric hail detection. Wea. Forecasting, 21, 839850, https://doi.org/10.1175/WAF956.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hendry, A., and G. C. McCormick, 1976: Radar observations of alignment of precipitation particles by electrostatic fields in thunderstorms. J. Geophys. Res., 81, 53535357, https://doi.org/10.1029/JC081i030p05353.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holle, R. L., N. W. Demetriades, and A. Nag, 2016: Objective airport warnings over small areas using NLDN cloud and cloud-to-ground lightning data. Wea. Forecasting, 31, 10611069, https://doi.org/10.1175/WAF-D-15-0165.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hubbert, J. C., and S. M. Ellis, 2014: Microphysical interpretation of coincident simultaneous and fast alternating horizontal and vertical polarization transmit data. Eighth European Conf. on Radar in Meteorology and Hydrology (ERAD 2014), Garmisch-Partenkirchen, Germany, DWD, http://n2t.net/ark:/85065/d7dn46k1.

    • Search Google Scholar
    • Export Citation
  • Hubbert, J. C., S. M. Ellis, M. Dixon, and G. Meymaris, 2010: Modeling, error analysis, and evaluation of dual-polarization variables obtained from simultaneous horizontal and vertical polarization transmit radar. Part I: Modeling and antenna errors. J. Atmos. Oceanic Technol., 27, 15831598, https://doi.org/10.1175/2010JTECHA1336.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hubbert, J. C., S. M. Ellis, W. Chang, S. Rutledge, and M. Dixon, 2014: Modeling and interpretation of S-band ice crystal depolarization signatures from data obtained by simultaneously transmitting horizontally and vertically polarized fields. J. Appl. Meteor. Climatol., 53, 16591677, https://doi.org/10.1175/JAMC-D-13-0158.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • International Electrotechnical Commission, 2010: Protection against lightning—Part II. Risk management. 2nd ed. IEC, 85 pp.

  • Kennedy, P. C., and S. A. Rutledge, 2011: S-band dual-polarization radar observations of winter storms. J. Appl. Meteor. Climatol., 50, 844858, https://doi.org/10.1175/2010JAMC2558.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koshak, W. J., and R. J. Solakiewicz, 2015: A method for retrieving the ground flash fraction and flash time from satellite lightning mapper observations. J. Atmos. Oceanic Technol., 32, 7996, https://doi.org/10.1175/JTECH-D-14-00085.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Krehbiel, P. R., T. Chen, S. McCrary, W. Rison, G. Gray, and M. Brook, 1996: The use of dual-channel circular-polarization radar observations for remotely sensing storm electrification. Meteor. Atmos. Phys., 59, 6582, https://doi.org/10.1007/BF01032001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Krehbiel, P. R., J. A. Riousset, V. P. Pasko, R. J. Thomas, W. Rison, M. A. Stanley, and H. E. Edens, 2008: Upward electrical discharges from thunderstorms. Nat. Geosci., 1, 233237, https://doi.org/10.1038/ngeo162.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuhlman, K. M., D. R. MacGorman, M. I. Biggerstaff, and P. R. Krehbiel, 2009: Lightning initiation in the anvils of two supercell storms. Geophys. Res. Lett., 36, L07802, https://doi.org/10.1029/2008GL036650.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumjian, M. R., 2013: Principles and applications of dual-polarization weather radar. Part III: Artifacts. J. Oper. Meteor., 1, 265274, https://doi.org/10.15191/nwajom.2013.0121.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kumjian, M. R., and W. Deierling, 2015: Analysis of thundersnow storms over Northern Colorado. Wea. Forecasting, 30, 14691490, https://doi.org/10.1175/WAF-D-15-0007.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lang, T. J., and Coauthors, 2017: WMO World record lightning extremes: Longest reported flash distance and longest reported flash duration. Bull. Amer. Meteor. Soc., 98, 11531168, https://doi.org/10.1175/BAMS-D-16-0061.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lengyel, M. M., H. Brooks, R. E. Holle, and M. A. Cooper, 2005: Lightning casualties and their proximity to surrounding cloud-to-ground lightning. 14th Symp. on Education, Atlanta, GA, Amer. Meteor. Soc., P1.35, https://ams.confex.com/ams/Annual2005/techprogram/paper_85775.htm.

    • Search Google Scholar
    • Export Citation
  • Liu, C., and S. Heckman, 2012: Total lightning data and real-time severe storm prediction. TECO-2012: WMO Tech. Conf. on Meteorological and Environmental Instruments and Methods of Observation, Brussels, Belgium, WMO, P5(10), http://www.wmo.int/pages/prog/www/IMOP/publications/IOM-109_TECO-2012/Session5/P5_10_Liu_Total_Lightning_Data_and_Real-Time_Severe_Storm_Prediction.pdf.

    • Search Google Scholar
    • Export Citation
  • Liu, H., and V. Chandrasekar, 2000: Classification of hydrometeors based on polarimetric radar measurements: Development of fuzzy logic and neuro-fuzzy systems, and in situ verification. J. Atmos. Oceanic Technol., 17, 140164, https://doi.org/10.1175/1520-0426(2000)017<0140:COHBOP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 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, E73E86, https://doi.org/10.1175/BAMS-D-19-0033.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • MacGorman, D. R., I. R. Apostolakopoulos, N. R. Lund, N. W. S. Demetriades, M. J. Murphy, and P. R. Krehbiel, 2011: The timing of cloud-to-ground lightning relative to total lightning activity. Mon. Wea. Rev., 139, 38713886, https://doi.org/10.1175/MWR-D-11-00047.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mach, D. M., 2019: Geostationary Lightning Mapper Clustering Algorithm Stability. 2019 Geostationary Lightning Mapper Science Team Meeting, Huntsville, AL, NASA, https://goes-r.nsstc.nasa.gov/home/meeting-agenda-2019.

    • Search Google Scholar
    • Export Citation
  • Medici, G., K. L. Cummins, D. J. Cecil, W. J. Koshak, and S. D. Rudlosky, 2017: The intracloud lightning fraction in the contiguous United States. Mon. Wea. Rev., 145, 44814499, https://doi.org/10.1175/MWR-D-16-0426.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Metcalf, J. I., 1997: Temporal and spatial variations of hydrometeor orientation of hydrometeors in thunderstorms. J. Appl. Meteor., 36, 315321, https://doi.org/10.1175/1520-0450(1997)036<0315:TASVOH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Murphy, K. M., 2018: Assessing Lightning Risk in Outdoor Vulnerable Environments. Texas Tech University, 143 pp.

  • Murphy, K. M., E. C. Bruning, C. J. Schultz, and J. Vanos, 2021: A spatiotemporal lightning risk assessment using lightning mapping data. Wea. Climate Soc., https://doi.org/10.1175/WCAS-D-20-0021.1, in press.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nag, A., M. J. Murphy, W. Schulz, and K. L. Cummins, 2015: Lightning locating systems: Insights on characteristics and validation techniques. Earth Space Sci., 2, 6593, https://doi.org/10.1002/2014EA000051.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • NOAA, 2020: Advanced Weather Interactive Processing System (AWIPS). Accessed on 16 October 2020, https://vlab.ncep.noaa.gov/web/mdl/awips.

  • Peterson, M. J., 2019: Research applications for the Geostationary Lightning Mapper operational lightning flash product. J. Geophys. Res. Atmos., 124, 10 20510 231, https://doi.org/10.1029/2019JD031054.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peterson, M. J., and Coauthors, 2020: New World Meteorological Organization certified megaflash lightning extremes for flash distance (709 km) and duration (16.73 s) recorded from space. Geophys. Res. Lett., 47, e2020GL088888, https://doi.org/10.1029/2020GL088888.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Preston, A. D., and H. E. Fuelberg, 2015: Improving lightning cessation guidance using polarimetric radar data. Wea. Forecasting, 30, 308328, https://doi.org/10.1175/WAF-D-14-00031.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rison, W., R. J. Thomas, P. R. Krehbiel, T. Hamlin, and J. Harlin, 1999: A GPS-based three dimensional lightning mapping system: Initial observations in central New Mexico. Geophys. Res. Lett., 26, 35733576, https://doi.org/10.1029/1999GL010856.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rudlosky, S. D., S. J. Goodman, K. S. Virts, and E. C. Bruning, 2019: Initial Geostationary Lightning Mapper observations. Geophys. Res. Lett., 46, 10971104, https://doi.org/10.1029/2018GL081052.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rumpf, C. M., R. S. Longenbaugh, C. E. Henze, J. C. Chavez, and D. L. Mathias, 2019: An algorithmic approach for detecting bolides with the Geostationary Lightning Mapper. Sensors, 19, 1008, https://doi.org/10.3390/s19051008.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., 2007: The impact of beam broadening on the quality of radar polarimetric data. J. Atmos. Oceanic Technol., 24, 729744, https://doi.org/10.1175/JTECH2003.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., and D. S. Zrnić, 2007: Depolarization in ice crystals and its effect on radar polarimetric measurements. J. Atmos. Oceanic Technol., 24, 12561267, https://doi.org/10.1175/JTECH2034.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sanderson, D. L., E. D. White, A. J. Geyer, W. P. Roeder, and A. J. Gutman, 2020: Optimizing the lightning warning radii at spaceport Florida. Wea. Forecasting, 35, 523536, https://doi.org/10.1175/WAF-D-19-0129.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saunders, C. P. R., H. Bax-Norman, C. Emersic, E. E. Avila, and N. E. Castellano, 2006: Laboratory studies of the effect of cloud conditions on graupel/crystal charge transfer in thunderstorm electrification. Quart. J. Roy. Meteor. Soc., 132, 26532673, https://doi.org/10.1256/qj.05.218.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schultz, C. J., and B. C. Carcione, 2020: Rumble heard ‘Round the Valley. Wide Word of SPoRT blog post. Accessed 20 April 2020, https://nasasport.wordpress.com/2020/04/20/the-rumble-heard-round-the-valley/.

  • Schultz, C. J., G. T. Stano, P. J. Meyer, B. C. Carcione, and T. Barron, 2017: Lightning decision support using VHF total lightning mapping and NLDN cloud-to-ground data in North Alabama. J. Oper. Meteor., 5, 134145, https://doi.org/10.15191/nwajom.2017.0511.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Scott, R. D., P. R. Krehbiel, and W. Rison, 2001: The use of simultaneous horizontal and vertical transmissions for dual-polarization radar meteorological observations. J. Atmos. Oceanic Technol., 18, 629648, https://doi.org/10.1175/1520-0426(2001)018<0629:TUOSHA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Stano, G. T., H. E. Fuelberg, and W. P. Roeder, 2010: Developing empirical lightning cessation forecast guidance for the Cape Canaveral Air Force Station and Kennedy Space Center. J. Geophys. Res., 115, D09205, https://doi.org/10.1029/2009JD013034.

    • Search Google Scholar
    • Export Citation
  • Stano, G. T., M. R. Smith, and C. J. Schultz, 2019: Development and evaluation of the GLM stoplight product for lightning safety. J. Oper. Meteor., 7, 92104, https://doi.org/10.15191/nwajom.2019.0707.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Steiger, S. M., R. E. Orville, and L. D. Carey, 2007: Total lightning signatures of thunderstorm intensity over North Texas. Part II: Mesoscale convective systems. Mon. Wea. Rev., 135, 33033324, https://doi.org/10.1175/MWR3483.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Straka J. M., D. S. Zrnić, and A. V. Ryzhkov , 2000: Bulk hydrometeor classification and quantification using polarimetric radar data: Synthesis of relations. J. Appl. Meteor., 39, 13411372, https://doi.org/10.1175/1520-0450(2000)039<1341:BHCAQU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Takahashi, T., 1978: Riming electrification as a charge generation mechanism in thunderstorms. J. Atmos. Sci., 35, 15361548, https://doi.org/10.1175/1520-0469(1978)035<1536:REAACG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thompson, E. J., S. A. Rutledge, B. Dolan, V. Chandrasekar, and B. L. Cheong, 2014: A dual-polarization radar hydrometeor classification algorithm for winter precipitation. J. Atmos. Oceanic Technol., 31, 14571481, https://doi.org/10.1175/JTECH-D-13-00119.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Unidata, 2020: Integrated Data Viewer. Accessed 3 June 2020, https://doi.org/10.5065/D6H70CW6.

    • Crossref
    • Export Citation
  • Vincent, B. R., L. D. Carey, D. Schneider, K. Keeter, and R. Gonski, 2003: Using WSR-88D reflectivity data for the prediction of cloud-to-ground lightning: A North Carolina study. Natl. Wea. Dig., 27, 3544.

    • Search Google Scholar
    • Export Citation
  • Vivekanandan, J., D. S. Zrnić, S. M. Ellis, R. Oye, A. V. Ryzhkov, and J. Straka, 1999: Cloud microphysics retrieval using S-band dual-polarization radar measurements. Bull. Amer. Meteor. Soc., 80, 381388, https://doi.org/10.1175/1520-0477(1999)080<0381:CMRUSB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weiss, S. A., D. R. MacGorman, and K. M. Calhoun, 2012: Lightning in the anvils of supercell thunderstorms. Mon. Wea. Rev., 140, 20642079, https://doi.org/10.1175/MWR-D-11-00312.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Woodard, C. J., L. D. Carey, W. A. Petersen, and W. P. Roeder, 2012: Operational utility of dual-polarization variables in lightning initiation forecasting. Electron. J. Oper. Meteor., 13, 79102.

    • Search Google Scholar
    • Export Citation
  • Zrnić, D. S., N. Balakrishnan, C. L. Ziegler, V. N. Bringi, K. Aydin, and T. Matejka, 1993: Polarimetric signatures in the stratiform region of a mesoscale convective system. J. Appl. Meteor., 32, 678693, https://doi.org/10.1175/1520-0450(1993)032<0678:PSITSR>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
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Investigation of Cloud-to-Ground Flashes in the Non-Precipitating Stratiform Region of a Mesoscale Convective System on 20 August 2019 and Implications for Decision Support Services

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  • 1 NASA Short-term Prediction and Research Transition Center, Marshall Space Flight Center, Huntsville, Alabama
  • | 2 NASA SPoRT/Jacobs Engineering, Huntsville, Alabama
  • | 3 NASA SPoRT/Earth System Science Center, University of Alabama in Huntsville, Huntsville, Alabama
  • | 4 National Weather Service, St. Louis, Missouri
  • | 5 Department of Geosciences, Texas Tech University, Lubbock, Texas
  • | 6 Department of Atmospheric Science, University of Alabama in Huntsville, Huntsville, Alabama
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Abstract

Infrequent lightning flashes occurring outside of surface precipitation pose challenges to Impact-Based Decision Support Services (IDSS) for outdoor activities. This paper examines the remote sensing observations from an event on 20 August 2019 where multiple cloud-to-ground flashes occurred over 10 km outside surface precipitation (lowest radar tilt reflectivity < 10 dBZ and no evidence of surface precipitation) in a trailing stratiform region of a mesoscale convective system. The goal is to demonstrate the fusion of radar with multiple lightning observations and a lightning risk model to demonstrate how reflectivity and differential reflectivity combined provided the best indicator for the potential of lightning where all of the other lightning safety methods failed. A total of 13 lightning flashes were observed by the Geostationary Lightning Mapper (GLM) within the trailing stratiform region between 2100 and 2300 UTC. The average size of the 13 lightning flashes was 3184 km2, with an average total optical energy of 7734 fJ. A total of 75 NLDN flash locations were coincident with the 13 GLM flashes, resulting in an average of 5.8 NLDN flashes [in-cloud (IC) and cloud-to-ground (CG)] per GLM flash. In total, five of the GLM flashes contained at least one positive cloud-to-ground flash (+CG) flash identified by the NLDN, with peak amplitudes ranging between 66 and 136 kA. All eight CG flashes identified by the NLDN were located more than 10 km outside surface precipitation. The only indication of the potential of these infrequently large flashes was the presence of depolarization streaks in differential reflectivity (ZDR) and enhanced reflectivity near the melting layer.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Christopher J. Schultz, christopher.j.schultz@nasa.gov

Abstract

Infrequent lightning flashes occurring outside of surface precipitation pose challenges to Impact-Based Decision Support Services (IDSS) for outdoor activities. This paper examines the remote sensing observations from an event on 20 August 2019 where multiple cloud-to-ground flashes occurred over 10 km outside surface precipitation (lowest radar tilt reflectivity < 10 dBZ and no evidence of surface precipitation) in a trailing stratiform region of a mesoscale convective system. The goal is to demonstrate the fusion of radar with multiple lightning observations and a lightning risk model to demonstrate how reflectivity and differential reflectivity combined provided the best indicator for the potential of lightning where all of the other lightning safety methods failed. A total of 13 lightning flashes were observed by the Geostationary Lightning Mapper (GLM) within the trailing stratiform region between 2100 and 2300 UTC. The average size of the 13 lightning flashes was 3184 km2, with an average total optical energy of 7734 fJ. A total of 75 NLDN flash locations were coincident with the 13 GLM flashes, resulting in an average of 5.8 NLDN flashes [in-cloud (IC) and cloud-to-ground (CG)] per GLM flash. In total, five of the GLM flashes contained at least one positive cloud-to-ground flash (+CG) flash identified by the NLDN, with peak amplitudes ranging between 66 and 136 kA. All eight CG flashes identified by the NLDN were located more than 10 km outside surface precipitation. The only indication of the potential of these infrequently large flashes was the presence of depolarization streaks in differential reflectivity (ZDR) and enhanced reflectivity near the melting layer.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Dr. Christopher J. Schultz, christopher.j.schultz@nasa.gov
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