• Abarca, S. F., K. L. Corbosiero, and T. J. Galarneau, 2010: An evaluation of the Worldwide Lightning Location Network (WWLLN) using the National Lightning Detection Network (NLDN) as ground truth. J. Geophys. Res., 115, D18206, https://doi.org/10.1029/2009JD013411.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Abreu, D., D. Chandan, R. H. Holzworth, and K. Strong, 2010: A performance assessment of the World Wide Lightning Location Network (WWLLN) via comparison with the Canadian Lightning Detection Network (CLDN). Atmos. Meas. Tech., 3, 11431153, https://doi.org/10.5194/amt-3-1143-2010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Albrecht, R. G. I., S. J. Goodman, D. E. Buechler, R. J. Blakeslee, and H. J. Christian, 2016: Where are the lightning hotspots on earth? Bull. Amer. Meteor. Soc., 97, 20512068, https://doi.org/10.1175/BAMS-D-14-00193.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Anyah, R. O., and F. H. M. Semazzi, 2006: Climate variability over the greater Horn of Africa based on NCAR AGCM ensemble. Theor. Appl. Climatol., 86, 3962, https://doi.org/10.1007/s00704-005-0203-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baker, M. B., H. J. Christian, and J. Latham, 1995: A computational study of the relationships linking lightning frequency and other thundercloud parameters. Quart. J. Roy. Meteor. Soc., 121, 15251548, https://doi.org/10.1002/qj.49712152703.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Baker, M. B., A. M. Blyth, H. J. Christian, J. Latham, K. L. Miller, and A. M. Gadian, 1999: Relationships between lightning activity and various thundercloud parameters: Satellite and modelling studies. Atmos. Res., 51, 221236, https://doi.org/10.1016/S0169-8095(99)00009-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Banerjee, A., A. T. Archibald, A. C. Maycock, P. Telford, N. L. Abraham, X. Yang, P. Braesicke, and J. A. Pyle, 2014: Lightning NOx, a key chemistry-climate interaction: Impacts of future climate change and consequences for tropospheric oxidising capacity. Atmos. Chem. Phys., 14, 98719881, https://doi.org/10.5194/acp-14-9871-2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blanchard, D. O., 1998: Assessing the vertical distribution of convective available potential energy. Wea. Forecasting, 13, 870877, https://doi.org/10.1175/1520-0434(1998)013<0870:ATVDOC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Blyth, A., Christian, H. J., K. Driscoll, A. Gadian, and J. Latham, 2001: Determination of ice precipitation rates and thunderstorm anvil ice contents from satellite observations of lightning. Atmos. Res., 59–60, 217229, https://doi.org/10.1016/S0169-8095(01)00117-X.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Boden, T. A., G. Marland, and R. J. Andres, 2015a: African Fossil-Fuel CO2 Emissions. Carbon Dioxide Information Analysis Center, accessed 7 February 2020, https://cdiac.ess-dive.lbl.gov/trends/emis/afr.html.

  • Boden, T. A., G. Marland, and R. J. Andres, 2015b: Global Fossil-Fuel Carbon Emissions. Carbon Dioxide Information Analysis Center, accessed 7 February 2020, https://cdiac.ess-dive.lbl.gov/trends/emis/glo_2010.html.

  • Bond, D. W., S. Steiger, R. Zhang, X. Tie, and R. E. Orville, 2002: The importance of NOx production by lightning in the tropics. Atmos. Environ., 36, 15091519, https://doi.org/10.1016/S1352-2310(01)00553-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Bright, D. R., M. S. Wandishin, R. Jewell, and S. J. Weiss, 2005: A physically based parameter for lightning prediction and its calibration in ensemble forecasts. Conf. on Meteorological Applications of Lightning Data, San Diego, CA, Amer. Meteor. Soc., 4.3, https://ams.confex.com/ams/Annual2005/techprogram/paper_84173.htm.

  • Brooks, H., 2013: Severe thunderstorms and climate change. Atmos. Res., 123, 129138, http://dx.doi.org/10.1016/j.atmosres.2012.04.002.

  • Brooks, H., J. Lee, and J. Craven, 2003: The spatial distribution of severe thunderstorm and tornado environments from global reanalysis data. Atmos. Res., 67–68, 7394, https://doi.org/10.1016/S0169-8095(03)00045-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Changnon, S. A., and D. Changnon, 2001: Long-term fluctuations in thunderstorm activity in the United States. Climatic Change, 50, 489503, https://doi.org/10.1023/A:1010651512934.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Christian, H. J., 2003: Global frequency and distribution of lightning as observed from space by the Optical Transient Detector. J. Geophys. Res., 108, 4005, https://doi.org/10.1029/2002JD002347.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cooray, V., C. Cooray, and C. J. Andrews, 2007: Lightning caused injuries in humans. J. Electrost., 65, 386394, https://doi.org/10.1016/j.elstat.2006.09.016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Craven, J., R. Jewell, and H. Brooks, 2002: Comparison between observed convective cloud-base heights and lifting condensation level for two different lifted parcels. Wea. Forecasting, 17, 885890, https://doi.org/10.1175/1520-0434(2002)017<0885:CBOCCB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cummins, K. L., and M. J. Murphy, 2009: An overview of lightning locating systems: History, techniques, and 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
  • Deierling, W., W. A. Petersen, J. Latham, S. Ellis, and H. J. Christian, 2008: The relationship between lightning activity and ice fluxes in thunderstorms. J. Geophys. Res., 113, D15210, https://doi.org/10.1029/2007JD009700.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Del Genio, A. D., M. S. Yao, and J. Jonas, 2007: Will moist convection be stronger in a warmer climate? Geophys. Res. Lett., 34, L16703, https://doi.org/10.1029/2007GL030525.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dlamini, W. M., 2009: Lightning fatalities in Swaziland: 2000–2007. Nat. Hazards, 50, 179191, https://doi.org/10.1007/s11069-008-9331-6.

  • Donat, M. G., and Coauthors, 2014: Changes in extreme temperature and precipitation in the Arab region: Long-term trends and variability related to ENSO and NAO. Int. J. Climatol., 34, 581592, https://doi.org/10.1002/joc.3707.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doswell, C. A., H. E. Brooks, and R. A. Maddox, 1996: Flash flood forecasting: An ingredients-based methodology. Wea. Forecasting, 11, 560581, https://doi.org/10.1175/1520-0434(1996)011<0560:FFFAIB>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Emanuel, K. A., 1994: Atmospheric Convection. Oxford University Press, 580 pp.

  • Finney, D. L., R. M. Doherty, O. Wild, D. S. Stevenson, I. A. MacKenzie, and A. M. Blyth, 2018: A projected decrease in lightning under climate change. Nat. Climate Change., 8, 210213, https://doi.org/10.1038/s41558-018-0072-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Forster, P. M., and K. P. Shine, 1997: Radiative forcing and temperature trends from stratospheric ozone changes. J. Geophys. Res., 102, 10 84110 855, https://doi.org/10.1029/96JD03510.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gijben, M., L. L. Dyson, and M. T. Loots, 2017: A statistical scheme to forecast the daily lightning threat over southern Africa using the Unified Model. Atmos. Res., 194, 7888, https://doi.org/10.1016/J.ATMOSRES.2017.04.022.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Herrmann, S. M., A. Anyamba, and C. J. Tucker, 2005: Recent trends in vegetation dynamics in the African Sahel and their relationship to climate. Global Environ. Change, 15, 394404, https://doi.org/10.1016/j.gloenvcha.2005.08.004.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Holzworth, R. H., 2017: World Wide Lightning Location Network. Accessed 28 October 2018, http://wwlln.net/.

  • Hutchins, M. L., R. H. Holzworth, J. B. Brundell, and C. J. Rodger, 2012: Relative detection efficiency of the World Wide Lightning Location Network. Radio Sci., 47, RS6005, https://doi.org/10.1029/2012RS005049.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • IPCC, 2014: Climate Change 2014: Synthesis Report. R. K. Pachauri and L. A. Meyer, Eds., IPCC, 151 pp.

  • Jenne, R., 1992: Data for reanalysis: Inventories. UCAR, https://rda.ucar.edu/docs/papers-scanned/pdf/rj0011.pdf.

  • Jenne, R., and Coauthors, 1993: The NMC/NCAR CDAS/reanalysis project. Office Note 401, 83 pp., https://repository.library.noaa.gov/view/noaa/11438.

  • Jiang, J. H., and Coauthors, 2012: Evaluation of cloud and water vapor simulations in CMIP5 climate models using NASA “A-Train” satellite observations. J. Geophys. Res., 117, D14105, https://doi.org/10.1029/2011JD017237.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Khain, A., D. Rosenfeld, and A. Pokrovsky, 2005: Aerosol impact on the dynamics and microphysics of deep convective clouds. Quart. J. Roy. Meteor. Soc., 131, 26392663, https://doi.org/10.1256/qj.04.62.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Krause, A., S. Kloster, S. Wilkenskjeld, and H. Paeth, 2014: The sensitivity of global wildfires to simulated past, present, and future lightning frequency. J. Geophys. Res. Biogeosci., 119, 312322, https://doi.org/10.1002/2013JG002502.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Laing, A. G., J. M. Fritsch, and A. J. Negri, 1999: Contribution of mesoscale convective complexes to rainfall in Sahelian Africa: Estimates from geostationary infrared and passive microwave data. J. Appl. Meteor., 38, 957964, https://doi.org/10.1175/1520-0450(1999)038<0957:COMCCT>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Latham, J., 1981: The electrification of thunderstorms. Quart. J. Roy. Meteor. Soc., 107, 277298, https://doi.org/10.1002/qj.49710745202.

  • Louf, V., C. Jakob, A. Protat, M. Bergmann, and S. Narsey, 2019: The relationship of cloud number and size with their large-scale environment in deep tropical convection. Geophys. Res. Lett., 46, 92039212, https://doi.org/10.1029/2019GL083964.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lucas, C., M. A. LeMone, and E. J. Zipser, 1996: Reply. J. Atmos. Sci., 53, 12121214, https://doi.org/10.1175/1520-0469(1996)053<1212:R>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lynn, B., and Y. Yair, 2010: Prediction of lightning flash density with the WRF model. Adv. Geosci., 23, 1116, https://doi.org/10.5194/adgeo-23-11-2010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mary, A. K., and C. Gomes, 2012: Lightning accidents in Uganda. 31st Int. Conf. on Lightning Protection (ICLP), Vienna, Austria, IEEE, https://doi.org/10.1109/ICLP.2012.6344235.

    • Crossref
    • Export Citation
  • McCaul, E. W., and C. Cohen, 2002: The impact on simulated storm structure and intensity of variations in the mixed layer and moist layer depths. Mon. Wea. Rev., 130, 17221748, https://doi.org/10.1175/1520-0493(2002)130<1722:TIOSSS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mezuman, K., C. Price, and E. Galanti, 2014: On the spatial and temporal distribution of thunderstorm cells. Environ. Res. Lett., 9, 124023, https://doi.org/10.1088/1748-9326/9/12/124023.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Michalon, N., A. Nassif, T. Saouri, J. F. Royer, and C. A. Pontikis, 1999: Contribution to the climatological study of lightning. Geophys. Res. Lett., 26, 30973100, https://doi.org/10.1029/1999GL010837.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Myhre, G., and Coauthors, 2013: Anthropogenic and natural radiative forcing. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 659–740.

  • Newell, R. E., J. W. Kidson, D. G. Vincent, and G. J. Boer, 1974: General Circulation of the Tropical Atmosphere and Interactions with Extratropical Latitudes. MIT Press, 320 pp.

  • Nicholson, S. E., 2000: The nature of rainfall variability over Africa on time scales of decades to millennia. Global Planet. Change, 26, 137158, https://doi.org/10.1016/S0921-8181(00)00040-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • NOAA, 2017: El Niño Southern Oscillation (ENSO). NOAA/ESRL/PSD, accessed 28 June 2017, https://www.esrl.noaa.gov/psd/enso/.

  • Orville, R. E., and Coauthors, 2001: Enhancement of cloud-to-ground lightning over Houston, Texas. Geophys. Res. Lett., 28, 25972600, https://doi.org/10.1029/2001GL012990.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Parrish, D. F., and J. C. Derber, 1992: The National Meteorological Center’s spectral statistical-interpolation analysis system. Mon. Wea. Rev., 120, 17471763, https://doi.org/10.1175/1520-0493(1992)120<1747:TNMCSS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pinto, O., I. R. C. A. Pinto, and M. A. S. Ferro, 2013: A study of the long-term variability of thunderstorm days in southeast Brazil. J. Geophys. Res. Atmos., 118, 52315246, https://doi.org/10.1002/JGRD.50282.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Poccard, I., S. Janicot, and P. Camberlin, 2000: Comparison of rainfall structures between NCEP/NCAR reanalyses and observed data over tropical Africa. Climate Dyn., 16, 897915, https://doi.org/10.1007/s003820000087.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Price, C., 1993: Global surface temperatures and the atmospheric electrical circuit. Geophys. Res. Lett., 20, 13631366, https://doi.org/10.1029/93GL01774.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Price, C., 2000: Evidence for a link between global lightning activity and upper tropospheric water vapour. Nature, 406, 290293, https://doi.org/10.1038/35018543.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Price, C., 2013: Lightning applications in weather and climate research. Surv. Geophys., 34, 755767, https://doi.org/10.1007/s10712-012-9218-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Price, C., and D. Rind, 1994: Possible implications of global climate change on global lightning distributions and frequencies. J. Geophys. Res., 99, 10 82310 831, https://doi.org/10.1029/94JD00019.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Price, C., and M. Asfur, 2006a: Can lightning observations be used as an indicator of upper-tropospheric water vapor variability? Bull. Amer. Meteor. Soc., 87, 291298, https://doi.org/10.1175/BAMS-87-3-291.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Price, C., and M. Asfur, 2006b: Inferred long term trends in lightning activity over Africa. Earth Planets Space, 58, 11971201, https://doi.org/10.1186/BF03352010.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Price, C., J. Penner, and M. Prather, 1997: NOx from lightning: 1. Global distribution based on lightning physics. J. Geophys. Res., 102, 59295941, https://doi.org/10.1029/96JD03504.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Price, C., Y. Yair, and M. Asfur, 2007: East African lightning as a precursor of Atlantic hurricane activity. Geophys. Res. Lett., 34, L09805, https://doi.org/10.1029/2006GL028884.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Price, C., and Coauthors, 2011: Using lightning data to better understand and predict flash floods in the Mediterranean. Surv. Geophys., 32, 733751, https://doi.org/10.1007/s10712-011-9146-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Price, C., N. Reicher, and Y. Yair, 2015: Do West African thunderstorms predict the intensity of Atlantic hurricanes? Geophys. Res. Lett., 42, 24572463, https://doi.org/10.1002/2014GL062932.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rodger, C. J., 2008: Growing detection efficiency of the World Wide Lightning Location Network. AIP Conf. Proc., 1118, 15, https://doi.org/10.1063/1.3137706.

    • Search Google Scholar
    • Export Citation
  • Rodger, C. J., S. Werner, J. B. Brundell, E. H. Lay, N. R. Thomson, R. H. Holzworth, and R. L. Dowden, 2006: Detection efficiency of the VLF World-Wide Lightning Location Network (WWLLN): Initial case study. Ann. Geophys., 24, 31973214, https://doi.org/10.5194/angeo-24-3197-2006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Romps, D. M., J. T. Seeley, D. Vollaro, and J. Molinari, 2014: Projected Increase in lightning strikes in the United States due to global warming. Science, 346, 851854, https://doi.org/10.1126/science.1259100.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Romps, D. M., A. B. Charn, R. H. Holzworth, W. E. Lawrence, J. Molinari, and D. Vollaro, 2018: CAPE times P explains lightning over land but not the land–ocean contrast. Geophys. Res. Lett., 45, 12 62312 630, https://doi.org/10.1029/2018GL080267.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rosenfeld, D., and W. Woodley, 2000: Deep convective clouds with sustained supercooled liquid water down to −37.5°C. Nature, 405, 440442, https://doi.org/10.1038/35013030.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rowell, D. P., C. K. Folland, K. Maskell, and M. N. Ward, 1995: Variability of summer rainfall over tropical North Africa (1906–92): Observations and modelling. Quart. J. Roy. Meteor. Soc., 121, 669704, https://doi.org/10.1002/qj.49712152311.

    • Search Google Scholar
    • Export Citation
  • Rudlosky, S. D., and D. T. Shea, 2013: Evaluating WWLLN performance relative to TRMM/LIS. Geophys. Res. Lett., 40, 23442348, https://doi.org/10.1002/grl.50428.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rutledge, S. A., E. Williams, and T. D. Keenan, 1992: The Down Under Doppler and Electricity Experiment (DUNDEE): Overview and preliminary results. Bull. Amer. Meteor. Soc., 73, 316, https://doi.org/10.1175/1520-0477(1992)073<0003:TDUDAE>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schumann, U., and H. Huntrieser, 2007: The global lightning-induced nitrogen oxides source. Atmos. Chem. Phys., 7, 38233907, https://doi.org/10.5194/acp-7-3823-2007.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seeley, J. T., and D. M. Romps, 2015: The effect of global warming on severe thunderstorms in the United States. J. Climate, 28, 24432458, https://doi.org/10.1175/JCLI-D-14-00382.1.

    • 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
  • Taylor, C. M., and Coauthors, 2017: Frequency of extreme Sahelian storms tripled since 1982 in satellite observations. Nature, 544, 475478, http://doi.org/10.1038/nature22069.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Toracinta, E. R., and E. J. Zipser, 2001: Lightning and SSM/I-ice-scattering mesoscale convective systems in the global tropics. J. Appl. Meteor., 40, 9831002, https://doi.org/10.1175/1520-0450(2001)040<0983:LASIIS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., N. S. Diffenbaugh, H. E. Brooks, M. E. Baldwin, E. D. Robinson, and J. S. Pal, 2007: Changes in severe thunderstorm environment frequency during the 21st century caused by anthropogenically enhanced global radiative forcing. Proc. Natl. Acad. Sci. USA, 104, 19 71919 723, https://doi.org/10.1073/pnas.0705494104.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Trapp, R. J., N. S. Diffenbaugh, and A. Gluhovsky, 2009: Transient response of severe thunderstorm forcing to elevated greenhouse gas concentrations. Geophys. Res. Lett., 36, L01703, https://doi.org/10.1029/2008GL036203.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Virts, K. S., J. M. Wallace, M. L. Hutchins, and R. H. Holzworth, 2013: Highlights of a new ground-based, hourly global lightning climatology. Bull. Amer. Meteor. Soc., 94, 13811391, https://doi.org/10.1175/BAMS-D-12-00082.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, C., D. Zheng, Y. Zhang, and L. Liu, 2017: Relationship between lightning activity and vertical airflow characteristics in thunderstorms. Atmos. Res., 191, 1219, https://doi.org/10.1016/J.ATMOSRES.2017.03.003.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, E., 1985: Large-scale charge separation in thunderclouds. J. Geophys. Res., 90, 60136025, https://doi.org/10.1029/JD090iD04p06013.

  • Williams, E., 1992: The Schumann resonance: A global tropical thermometer. Science, 256, 11841187, https://doi.org/10.1126/science.256.5060.1184.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, E., 1994: Global circuit response to seasonal variations in global surface air temperature. Mon. Wea. Rev., 122, 19171929, https://doi.org/10.1175/1520-0493(1994)122<1917:GCRTSV>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, E., 2005: Lightning and climate: A review. Atmos. Res., 76, 272287, https://doi.org/10.1016/j.atmosres.2004.11.014.

  • Williams, E., and N. Renno, 1993: An analysis of the conditional instability of the tropical atmosphere. Mon. Wea. Rev., 121, 2136, https://doi.org/10.1175/1520-0493(1993)121<0021:AAOTCI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, E., and S. Stanfill, 2002: The physical origin of the land–ocean contrast in lightning activity. C. R. Phys., 3, 12771292, https://doi.org/10.1016/S1631-0705(02)01407-X.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, E., and G. Sátori, 2004: Lightning, thermodynamic and hydrological comparison of the two tropical continental chimneys. J. Atmos. Sol.-Terr. Phys., 66, 12131231, https://doi.org/10.1016/j.jastp.2004.05.015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, E., and Coauthors, 1999: The behavior of total lightning activity in severe Florida thunderstorms. Atmos. Res., 51, 245265, https://doi.org/10.1016/S0169-8095(99)00011-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, E., K. Rothkin, D. S. Stevenson, and D. Boccippio, 2000: Global lightning variations caused by changes in thunderstorm flash rate and by changes in the number of thunderstorms. J. Appl. Meteor., 39, 22232230, https://doi.org/10.1175/1520-0450(2001)040<2223:GLVCBC>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, E., and Coauthors, 2002: Contrasting convective regimes over the Amazon: Implications for cloud electrification. J. Geophys. Res., 107, 8082, https://doi.org/10.1029/2001JD000380.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, E., V. Mushtak, D. Rosenfeld, S. Goodman, and D. Boccippio, 2005: Thermodynamic conditions favorable to superlative thunderstorm updraft, mixed phase microphysics and lightning flash rate. Atmos. Res., 76, 288306, https://doi.org/10.1016/j.atmosres.2004.11.009.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Williams, E., A. Guha, R. Boldi, H. Christian, and D. Buechler, 2019: Global lightning activity and the hiatus in global warming. J. Atmos. Solar-Terr. Phys., 189, 2734, https://doi.org/10.1016/J.JASTP.2019.03.011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yair, Y., B. Lynn, C. Price, V. Kotroni, K. Lagouvardos, E. Morin, A. Mugnai, and M. del Carmen Llasat, 2010: Predicting the potential for lightning activity in Mediterranean storms based on the Weather Research and Forecasting (WRF) model dynamic and microphysical fields. J. Geophys. Res., 115, D04205, https://doi.org/10.1029/2008JD010868.

    • Search Google Scholar
    • Export Citation
  • Yin, X., and S. E. Nicholson, 1998: The water balance of Lake Victoria. Hydrol. Sci. J., 43, 789811, https://doi.org/10.1080/02626669809492173.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yoshida, S., T. Morimoto, T. Ushio, and Z. I. Kawasaki, 2009: A fifth-power relationship for lightning activity from Tropical Rainfall Measuring Mission satellite observations. J. Geophys. Res., 114, D09104, https://doi.org/10.1029/2008JD010370.

    • Search Google Scholar
    • Export Citation
  • Ziv, B., H. Saaroni, Y. Yair, M. Ganot, A. Baharad, and D. Isaschari, 2009: Atmospheric factors governing winter thunderstorms in the coastal region of the eastern Mediterranean. Theor. Appl. Climatol., 95, 301310, https://doi.org/10.1007/s00704-008-0008-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 88 88 31
Full Text Views 14 14 3
PDF Downloads 16 16 3

Thunderstorm Trends over Africa

View More View Less
  • 1 Porter School of the Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel
© Get Permissions
Restricted access

Abstract

Thunderstorms inflict death and damage worldwide due to lightning, heavy rains, hail, and strong winds. While the effect of global warming on future thunderstorm activity is still debatable, this work investigates how thunderstorm activity over Africa may have changed over the last 70 years. Thunderstorm data were obtained from the World Wide Lightning Location Network (WWLLN) and processed to produce thunderstorm clusters. The number and area of clusters in one year (2013) were compared with several climate parameters tied to thunderstorm development, taken from the NCEP–NCAR Reanalysis-1 product (NCEP). The two parameters that correlated best with thunderstorm number were lifted index and specific humidity, with correlations of −0.795 and 0.779, respectively. These parameters were used to construct an empirical model that predicts the number and area of thunderstorm clusters over Africa on a particular day, month, or year. The empirical model was run from 1948 to 2016, providing a reconstruction of long-term thunderstorm activity over Africa. The time series was compared to temperature data from NCEP, and showed that the number of clusters increased with rising surface temperature on annual and decadal time scales, particularly since the mid-1990s. On an annual time scale, the number and area of thunderstorm clusters exhibited a highly sensitive relationship with surface temperature, with a ~40% increase in the number of thunderstorm clusters for every 1-K rise in temperature over Africa. The correlation coefficients with surface temperature were 0.745 and 0.743 for cluster number and area, respectively, indicating that surface temperature explains ~55% of the variability in interannual thunderstorm clusters over the past 70 years.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-18-0781.s1.

© 2020 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: Maayan Harel, mharel.tau@gmail.com

Abstract

Thunderstorms inflict death and damage worldwide due to lightning, heavy rains, hail, and strong winds. While the effect of global warming on future thunderstorm activity is still debatable, this work investigates how thunderstorm activity over Africa may have changed over the last 70 years. Thunderstorm data were obtained from the World Wide Lightning Location Network (WWLLN) and processed to produce thunderstorm clusters. The number and area of clusters in one year (2013) were compared with several climate parameters tied to thunderstorm development, taken from the NCEP–NCAR Reanalysis-1 product (NCEP). The two parameters that correlated best with thunderstorm number were lifted index and specific humidity, with correlations of −0.795 and 0.779, respectively. These parameters were used to construct an empirical model that predicts the number and area of thunderstorm clusters over Africa on a particular day, month, or year. The empirical model was run from 1948 to 2016, providing a reconstruction of long-term thunderstorm activity over Africa. The time series was compared to temperature data from NCEP, and showed that the number of clusters increased with rising surface temperature on annual and decadal time scales, particularly since the mid-1990s. On an annual time scale, the number and area of thunderstorm clusters exhibited a highly sensitive relationship with surface temperature, with a ~40% increase in the number of thunderstorm clusters for every 1-K rise in temperature over Africa. The correlation coefficients with surface temperature were 0.745 and 0.743 for cluster number and area, respectively, indicating that surface temperature explains ~55% of the variability in interannual thunderstorm clusters over the past 70 years.

Supplemental information related to this paper is available at the Journals Online website: https://doi.org/10.1175/JCLI-D-18-0781.s1.

© 2020 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: Maayan Harel, mharel.tau@gmail.com

Supplementary Materials

    • Supplemental Materials (ZIP 4.83 MB)
Save