Reevaluating the Global and Temporal Distributions of Lightning Superbolts: Insights from ENTLN Data (2018–2021)

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This study reevaluates the global and temporal distributions of SBs using data from the Earth Networks Total Lightning Network (ENTLN) collected between 2018 and 2021. By focusing on strokes with Ip ≥ 30 kA (HIp), which constitute approximately 0.8% of all recorded events, the study analyzes their spatial distribution, diel patterns, and land-ocean ratios and reevaluates the Ip cutoff for SBs. The results indicate that HIp strokes are more densely concentrated over land than oceans, with continental hotspots identified in regions such as the Andes, Lake Maracaibo, the tall grass prairies of the United States and Southeast Asia. Conversely, oceanic HIp are relatively evenly distributed across latitudes but exhibit localized density increases in areas such as the Mediterranean Sea, Gulf of Mexico, Maritime Indonesia and of the western coasts of Africa and Central America. The study also finds that HIp with Ip > 50 kA exhibit a sea-to-land ratio greater than one, peaking at a ratio of ~ 15 for Ip > 120 kA before declining at higher Ip thresholds. Finally, temporal analyses reveal distinct diel patterns for HIp over land and sea, with oceanic distributions of the total lightning closely mirroring the Carnegie Curve's fair-weather atmospheric electric field diel variation. Earth and environmental sciences/Climate sciences Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Ocean sciences Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction In an analysis of cloud to ground lightning observations using a global VHF antenna network (GLD360) it was determined that the geometric mean peak current (Ip) of negative polarity cloud to ground lightning strikes (CGs) for the first return stroke was ~ 10–30 kA over the continents (Said et al., 2013 ). In contrast, the geometric mean of CGs Ip measured over the oceans in Said et al. ( 2013 ) varied in the range of ~ 25–45 kA. These energy categories of lightning strikes represent 95% of all CGs measured over the land and oceans globally during a one-year period ( Op. Cit. ). The spatial-temporal global distribution of total lightning (CG + intra cloud) in general has been previously determined based on satellite observations, where lightning occur most frequently over the land, during summertime in the northern temperate zone (Christian et al., 2003 ), while over the oceans, lightning occurs much less frequently, by a factor of ~ 10 ( Op. Cit. ). Previous studies, most notably Holzworth et al. ( 2019 ) showed based on the World-Wide Lightning Location Network (WWLLN) that high energy CGs (> 1 MJ) detected by the Very Low Frequency Time Of Arrival (VLF-TOA) network, also known as Super Bolts (SBs), which represent substantially less than 1% of the total CGs included in their dataset, occur predominantly over the oceans (> 90%). This is consistent with Hutchins et al. ( 2013 ), who showed that the ratio of lightning strokes observed by WWLLN, over the oceans and continents increases with increasing lightning stroke energy above 3000 J, where this ratio reaches a plateau value of ~ 2 for lightning strokes with energies in the range of 10 4 -10 6 J. It is interesting to note that the analysis of Hutchins et al. ( 2013 ) excluded lightning flashes with energies above 10 6 J, which were the focus of the Holzworth et al. ( 2019 ) analysis. Holzworth et al. ( 2019 ) defined two energy classes for SBs collected between 2010–2018, where the lower energy class included all SBs with energy > 1MJ and the higher energy class included all SBs with energy > 2MJ. Based on this classification Holzworth et al. ( 2019 ), identified a total of 8171 SBs throughout the study period with energies greater than 1 MJ, out of which 1719 events had energies greater than 2 MJ. These observations comprised 0.001% of all CGs recorded by WWLLN throughout the measuring period, and have energies three orders of magnitude above the mean value for a cloud-to-ground stroke (1000 J). According to the conversion equation of Hutchins et al. ( 2013 ), the mean radiated stroke energy in the Holzworth et al. ( 2019 ) dataset is equivalent to a peak current of 35 kA assuming a triggering window of 0.00133 ms. This mean value is substantially higher than the detection threshold (2 kA) of VLF-TOA lightning detection systems proposed by Krider et al. ( 2010 ). The cutoff energy for SBs used in Holzworth et al. ( 2019 ) is 10 6 J, which is equivalent to ~ 3000 kA according to the conversion equation of Hutchins et al. ( 2013 ) and assuming a triggering window of 0.00133 ms. This Ip is extremely high, however, it is well known from basic electrodynamic principles that the lightning duration increases with the power of the lightning bolt and therefore the calculated Ip will decrease according to the Huchins et al. (2013) equation and therefore assuming a two order of magnitude increase in the triggering window duration (0.133 ms), the cutoff Ip decreases to ~ 180 kA, which seems to be a much more reasonable value. Nonetheless, according to the classification and global distribution of Holzworth et al. ( 2019 ), most of the SBs occurred in the northern hemisphere (72%) during the wintertime (Fig. 1 a). Furthermore, it is also possible to identify global hotspots for SBs (Fig. 5 in Holzworth et al., 2019 ), including the Mediterranean Sea region (~ 24% of all SBs), the North Sea region (~ 16%), the Chilean high plateau (~ 10%), and off the coast of South Africa (~ 4%). Holzworth et al. ( 2019 ), also noted that most (86%) of the SBs occurred during the solar maximum (2013-15) and suggested that this correlation may be potentially causal. Finally, while lower energy CGs in general are most prevalent during the late afternoon to early evening hours ( e.g. , Williams et al., 2000 ; Price, 2009 ), according to the Holzworth et al. ( 2019 ) dataset, SBs exhibit a daily cycle with a maximum frequency after midnight until 0600 and a minimum frequency at midday (Fig. 1 b). This daily variation is in opposite phase to the fair-weather atmospheric electric field strength variation, also known as the Carnegie Curve. Turman ( 1977 ), first characterized SBs based on optical measurements from the Vela satellites and land based worldwide VLF monitoring network measurements (Freeman, 1974 ). Turman ( 1977 ) considered the upper 2% of the optical spectrum from the Vela measurements of optical power and showed that the corresponding energy of VLF RF sferics measurements (Freeman, 1974 ) were significantly and positively correlated (n = 17, R 2 = 0.43, p = 0.0038; correlation input data from Turman et al. (1977)). Thus, it was determined that the peak optical power of SBs is greater than 10 GW or 100 MJ in energy units of RF sferics that were output by the VLF system. In a later study, Kirkland ( 1999 ) determined the optical power threshold for SBs to be > 100 GW, an order of magnitude higher than the Turman threshold. Finally, in a recent study, a comparison was conducted between satellite optical power of lightning flashes and corresponding energy levels of CGs measured by WWLLN (Peterson, 2023 ). It was shown that lightning bolts with an optical intensity of > 100 GW, qualifying them as optical SBs (Kirkland, 1999 ), had energies 2–3 orders of magnitude lower than the 10 6 J threshold defined by Holzworth et al. ( 2019 ). Together with the discrepancies between the classification of SBs by Turman ( 1977 ), Kirkland ( 1999 ) and Holzworth et al. ( 2019 ) in terms of frequency (2%, 0.46% and 0.001%, respectively) and their energy (10 GW (100 MJ), 100 GW (1GJ) and 1MJ, respectively) it is somewhat difficult to determine a cutoff energy or Ip for SBs based on state-of-the-art VLF Ip measurements ( e.g. , ENTLN). For example, in order to discuss the land-ocean differences, frequencies, spatial distributions and conditions under which SBs occur, it is imperative to provide a more robust SB Ip threshold for these state-of-the-art systems. According to Cooray and Rakov ( 2012 ), assuming a maximum background electric field below thunderclouds of 150 kV/m, the theoretical upper limit for CGs peak current is 450–500 kA in the tropics and 300 kA in the temperate zones. Nonetheless, CGs with Ip > 500 kA and even > 1000 kA over the land have been measured and reported with VLF-TOA systems ( e.g. , Lyu et al., 2021 ). In this study, we examined the Earth Networks Total Lightning Network CG data from the period 2018–2021 to determine the cutoff Ip for SBs over the land and the oceans, which includes the upper 1% of all CGs included in the dataset. Where, according to Asfur et al. ( 2020 ), it is understood that the conductivity of the ground influences to a great extent the intensity of the lightning discharge. In addition, we will determine the annual, daily and global distributions of these SBs and their ocean-land ratios. Methods and Analysis Protocols Earth Networks Total Lightning Network (ENTLN) is comprised of over 1800 lightning sensors deployed globally (Liu & Heckman, 2011 ). The ENTLN is capable of observing lightning return strokes or multiple strokes (Mallick et al., 2015 ). In this study, CG data were obtained and analyzed for the period January 2018 until March 2021 without differentiating between the first and following return strokes ( https://www.earthnetworks.com/product/lightning-data/ ). The entire dataset (Ip = 0-1000 kA) included 3.78·10 9 CG events with positive and negative polarities. Out of this dataset, CG strokes with Ip ≥ 30 kA, which is equivalent to 550 J, according to the Hutchins et al. ( 2013 ) conversion equation, were extracted for further analysis. Altogether, the ENTLN subset (> 30 kA) constitutes ~ 0.8% of all CGs in the original dataset. The subset was binned into 2 kA bins for positive and negative polarities separately as well as separated for land and sea. Based on the distribution with PC of percent of the total we tried to determine a PC threshold for SBs over the continents and the oceans. Finally, the subsets of SBs over the continents and oceans were sorted by hour to determine the diel distribution of continental and oceanic SBs. Results The global lightning density distribution (per 0.25°X0.25°) for all events with Ip > 30 kA (negative and positive polarities) that occurred during the study period, indicate significantly higher densities of high peak-current strokes over the land than over the oceans (Fig. 2 ), with the highest densities over the continents in the southern hemisphere. The "Hotspots" of high continental lightning densities are apparent over the Andes region, Northern Columbia and Venezuela (Lake Maracaibo) in south America, in South Africa, the Maritime Continent in Southeast Asia and Northern Australia. This “hotspot” distribution is similar to the one described by Albrecht et al. ( 2016 ) that was based on optical intensity records. Over the oceans, CGs with Ip > 30 kA is relatively equally distributed (mostly lower than 1000 strikes per 0.25°X0.25°) between the latitude of 60°S and 60°N, with empty patches in the south Atlantic and Pacific oceans extending out from Western Africa and South America, respectively. There is also a sporadically bare patch of ocean extending from North America out into the Pacific Ocean and a bare zonal band along the equator in the Pacific Ocean. It should be noted that the regions bare of CGs in the southern hemisphere in the Atlantic and Pacific oceans as well as along the equatorial pacific correspond to upwelling regions along the continents and along the equator. Despite the relatively low densities in the oceans, it is possible to identify oceanic regions with relatively higher densities (1000–3000 strikes per 0.25°X0.25°) in the Mediterranean Sea, Gulf of Mexico, Arabian Sea, the regions across from Liberia and Cameroon in the Atlantic Ocean, in the region off the coasts of Mexico and California in the Pacific Ocean and others. It is interesting to note that in the region of the North Sea and English Channel the density of CGs with Ip > 30 kA is very low and in large areas even bare. This finding is contradictory to the distributions of SBs in the North Sea and English Channel during the period 2010–2018, presented in Holzworth et al. ( 2019 ). As stated above, the relative proportion of CGs with Ip > 30 kA from the total analyzed dataset is ~ 3.3%, while continental CGs comprises 2.8% and oceanic CGs is 4.1% of the total number of CGs with Ip > 2 kA. In Fig. 3 , the proportion of lightning events out of the total CGs is presented as a function of an increasing Ip threshold in a log-linear plot. According to Fig. 3 b, it is evident that the proportion of all CGs with Ip > 50 kA is strongly influenced by the proportion of the total occurring over the oceans and the peak sea to land ratio actually has two distinct peaks with values of 15 and 13 at Ip > 120 and 150, respectively. In Fig. 3 c, the proportion of CGs decreases with increasing Ip along a sigmoidal curve, dropping very quickly to 0.01% at ~ 500 kA and continues to decrease slowly to 0.0006% at 900 kA and drops quickly beyond to 0.00001% at 1000 kA. It should be noted that there is a high degree of skepticism regarding peak currents greater than the upper theoretical limits of Cooray and Rakov ( 2012 ) (300–500 kA). Nonetheless, it is interesting to note that the percentage at 500 kA threshold, which is the highest theoretical limit for lightning bolts in the tropics according to Cooray & Rakov ( 2012 ) is 0.001%, i.e. , 1 out 10 5 lightning bolts are SBs. The daily distribution of CGs with Ip > 30, 50, 100 and 200 kA, yields different distributions for the land and the sea (Fig. 4 ). The graph illustrates how the frequency of lightning strikes varies throughout the day over land and sea above different current thresholds, compared to the fair-weather Carnegie curve, which was calculated according to Harrison ( 2020 ). Generally, the normalized frequency of high Ip lightning strikes over land exhibit a notable increase during the afternoon and evening hours, with a marked decrease in the early morning and late night. In contrast the normalized frequency of high Ip lightning strikes over the sea exhibits peak values during the late afternoon and early evening hours and decrease to minimum values during the early morning hours. Overall, the sea distributions correspond well with the normalized fair-weather Carnegie curve, while the land distribution are out of phase. Discussion and Conclusions Previous studies, based on optical and VLF observations, determined that lightning superbolts (SBs) occur predominantly over the oceans. Turman ( 1977 ) based his conclusion on 3 years of Vela optical observations (1972-75), which consisted of thousands of flashes (as reported). Where, 1% of the flashes were categorized as SBs that occurred predominantly over the north west Pacific near the coast of Japan. Holzworth et al. ( 2019 ) based his conclusion on 10 years of WWLLN data, which recorded millions of flashes by ~ 70 antennas distributed globally. Where, 0.001% of the CGs were categorized as SBs, out of which > 90% occurred over the oceans, specifically in regions including, the Mediterranean Sea, the Northern Sea, the Indian and Atlantic oceans along the equator, and along the 45°N and 45°S parallels across the Pacific and Atlantic oceans. In this study, which is based on the ENTLN data consisting of ~ 10 9 CGs, collected by ~ 1200 antennas distributed globally, during the period 2018–2021, the proportion of high peak current CGs over the oceans compared to land was greater than 1 starting at Ip > 50 kA and no more than ~ 15 for Ip > 120 kA (Fig. 3 ). For Ip > 200 kA, the peak sea to land ratio of 2.4 occurs at Ip > 380 kA and decreases to a relatively constant ratio of 1.2 from Ip > 550 kA. These findings are inconsistent with the findings of Turman ( 1977 ) and Holzworth et al. ( 2019 ), with respect to the sea-land cloud-to-ground stroke ratios. However, it should be noted that within the threshold range of 90–180 kA, the average sea to land ratio is ~ 9, i.e., 90% of the CGs in this threshold range occur over the oceans, similar to the result of Holzworth et al. ( 2019 ). The theoretical upper thresholds for peak current values in cloud-to-ground strokes in the tropics and temperate zones according to Cooray and Rakov ( 2012 ) are 500 and 300 kA, respectively. Thus, the proportions of strong strokes with peak currents in the above ranges of the total based on the ENTLN data in the present study varies in the range 0.0003–0.003%, where the sea-land ratio varies in the range ~ 1.5–2.4 (Fig. 3 ). It appears that the occurrence of CGs with peak currents in the range 50–190 kA is substantially more frequent over sea than land, suggesting that these high peak current discharges over the oceans are more the rule than the exception. Thus, if SBs are characterized as extremely rare events (0.0001%) according to Holzworth et al. ( 2019 ), then according to this dataset, the threshold for SBs, should be set higher than 700 kA, where the sea-land ratio is relatively constant with increasing Ip at ~ 1.5. However, despite the fact that Ip > 500 kA have been previously measured by VLF-TOA systems and reported in the scientific literature ( e.g. , Smorgonskii et al., 2018 ), it is generally accepted that these extreme values are not real and most likely measurement artifacts. Nonetheless, it should be noted that the theoretical upper limits of Ip for CGs determined by Cooray & Rakov ( 2012 ) were calculated under the assumptions that Ip is limited by the maximum measured atmospheric breakdown potential of 150 kV/m and the mean lightning discharge duration of 100 µs following the reanalysis of measurement from Cooray et al. ( 2007 ). These values appear to be relatively arbitrary considering the large variation of observed discharge durations ( e.g. , Smorgonskii et al., 2018 –30 µs – 1928 ms) and observed values of electric field strength, which do not even attain the experimental breakdown potential for dry air of 3 MV/m ( e.g. , Hogg et al., 2013 ). Considering the continental subset of the Ip > 30 kA, the relative proportion of continental CGs out of the total continental CGs (0-1000 kA) is 2.8% (Fig. 3 ). Similarly, the relative proportion of ocean CGs with Ip > 30 kA out of the total oceanic CGs (0-1000 kA) is 4.1%. Where, it should be noted that most of the CGs with Ip > 30 kA occurred in the latitudinal range of 40°S to 40°N (Fig. 2 ). It is interesting to note that the Ip for 0.01% of CGs over the continents is 165 kA, while over the oceans it is 260 kA. Thus, assuming that 0.01% of all CGs can be characterized as SBs, it is apparent that the Ip threshold over the oceans is substantially greater than the threshold over the continents. This finding is consistent with the findings of Said et al. ( 2013 ) and the conclusions of Asfur et al. ( 2020 ), who suggested that the lightning intensity is strongly influenced by the conductivity of the receiving surface (solid ground − 0–10 mS/cm compared to seawater – 50–60 mS/cm). Finally, the sea to land ratio of CGs increases from a minimum value of ~ 0.8 at Ip > 30 kA to a maximum value of ~ 15 at Ip > 1 kA (Fig. 3 ). After the maxima, the ratio drops rapidly to ~ 1.9 at ~ 190 kA and remains relatively steady thereafter. The relative contribution of oceanic and continental lightning activity to the diel variation in the fair-weather electric field, the Carnegie curve, has been previously investigated by Liu et al. ( 2010 ). In their study, it was shown that the diel variations in the electrical activity of clouds over both land and oceans in the latitudinal range of 35°S to 35°N, determined from TRMM rainfall reflectance measurements, were in phase with the Carnegie curve. In this study, the contribution of CGs over the oceans with 80 < Ip < 150 kA relative to CGs over the land in the same Ip range is apparently in phase with the Carnegie curve during the afternoon, but out of phase throughout the night and early morning hours (Fig. 5 ). This result suggests that that the relative contribution of SBs over the ocean to the Carnegie curve in the afternoon and early evening is significant, while the relative contributions during the nighttime is insignificant. However, it can be inferred from Fig. 4 that the combined diel distributions of land and ocean CG frequencies is in phase with the Carnegie curve, where the highest correlation coefficient is observed for SBs with Ip > 50 kA (R 2 = 0.84) (Figure S1 ). In conclusion, the analysis of this global dataset shows that high intensity CGs with Ip in the range of 125–155 kA observed over the period 2018-21, occur 13–15 times more often over the oceans relative to the continents. Above this range the sea to land ratio decreases to an average value of 1.6 for Ip > 180 kA, which is somewhat lower than the theoretical upper limit for Ip of 300 kA, estimated for temperate latitudes (Cooray & Rakov, 2012 ). Where, the recorded CGs with Ip > 500 kA, which is the upper theoretical limit of Ip estimated for the tropics, represents ca. 0.0003% of the total lightning. This percentage is an order of magnitude smaller than the proportion determined by Holzworth et al. ( 2019 ) for SBs that predominantly occur over the oceans. Finally, the diel distributions of high intensity CGs indicate that they occur predominantly over the oceans throughout the entire day and are in phase with the fair-weather atmospheric electric field strength throughout the afternoon and early hours, but are in opposite phase during the nighttime and early morning hours. However, the combined diel distributions of SBs (land and ocean) exhibit a strong positive correlation with the phase of the Carnegie curve. Declarations Acknowledgements and Funding Information The author gratefully acknowledges the Earth Networks Total Lightning Network (ENTLN) for providing access to lightning data used in this study. We sincerely appreciate permission to use the data. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Declaration section Mustafa Asfur: Conceptualization, data curation, formal analysis, methodology, writing—original draft, visualization. Jacob Silverman: Conceptualization, data curation, formal analysis, methodology, writing—original draft, visualization. Both authors contributed to manuscript revision and approved the submitted version. Data availability statement All data presented are based on raw data of lightning measurements provided by ENTLN (https://ghrc.nsstc.nasa.gov/home/content/earth-networks-total- lightning-network-entln-global-lightning-network), which may be provided directly from this vendor. References Albrecht, R. I., Goodman, S. J., Buechler, D. E., Blakeslee, R. J., & Christian, H. J. (2016). Where are the lightning hotspots on Earth? Bulletin of the American Meteorological Society, 97(11), 2051-2068. https://doi.org/10.1175/BAMS-D-14-00193.1 Asfur, M., Price, C., Silverman, J., & Wishkerman, A. (2020). Why is lightning more intense over the oceans? Journal of Atmospheric and Solar-Terrestrial Physics, 202, 105259. https://doi.org/10.1016/j.jastp.2020.105259 Christian, H. J., Blakeslee, R. J., Boccippio, D. J., Boeck, W. L., Buechler, D. E., Driscoll, K. T., ... & Stewart, M. F. (2003). Global frequency and distribution of lightning as observed from space by the Optical Transient Detector. Journal of Geophysical Research: Atmospheres, 108(D1), ACL-4. https://doi.org/10.1029/2002JD002347 Cooray, V., Rakov, V., & Theethayi, N. (2007). The lightning striking distance—Revisited. Journal of Electrostatics, 65(5-6), 296-306. https://doi.org/10.1016/j.elstat.2006.09.008 Cooray, V., & Rakov, V. (2012). On the upper and lower limits of peak current of first return strokes in negative lightning flashes. Atmospheric research, 117, 12-17. https://doi.org/10.1016/j.atmosres.2011.06.002 Freeman, W. B. (1974). The distribution of thunderstorm and lightning parameters over the eastern hemisphere for 1972 (Doctoral dissertation, Texas A&M University). https://hdl.handle.net/1969.1/ETD-TAMU-1974-THESIS-F855 Harrison, R. G. (2020). Behind the curve: a comparison of historical sources for the Carnegie curve of the global atmospheric electric circuit. History of Geo-and Space Sciences, 11(2), 207-213. https://doi.org/10.5194/hgss-11-207-2020 Hogg, M. G., Timoshkin, I. V., Macgregor, S. J., Wilson, M. P., Given, M. J., & Wang, T. (2013, June). Electrical breakdown of short non-uniform air gaps. In 2013 19th IEEE Pulsed Power Conference (PPC) (pp. 1-4). IEEE. https://doi.org/10.1109/PPC.2013.6627482 Holzworth, R. H., McCarthy, M.P., Brundell, J. B., Jacobson, A. R., & Rodger, C. J. (2019). Global Distribution of Superbolts. J. Geophys. Res. Atmos. 124 (17-18), 9996-10005. https://doi.org/10.1029/2019JD030975 Hutchins, M. L., Holzworth, R. H., Virts, K. S., Wallace, J. M., & Heckman, S. (2013). Radiated VLF energy differences of land and oceanic lightning. Geophysical Research Letters, 40(10), 2390-2394. https://doi.org/10.1002/grl.50406 Kirkland, M. W. (1999). An examination of superbolt‐class lightning events observed by the FORTE satellite. Los Alamos National Laboratory, Atmospheric Sciences Group, New Mexico. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=114dac189f035ccdce46c7d67e35b0c1504874d3 Krider, E. P., Cummins, K. L., Biagi, C. J., Fleenor, S. A., & Wilson, J. G. (2010, September). Small negative strokes in cloud-to-ground lightning flashes. In 2010 30th International Conference on Lightning Protection (ICLP) (pp. 1-3). IEEE. https://doi.org/10.1109/ICLP.2010.7845966 Liu, C., Williams, E. R., Zipser, E. J., & Burns, G. (2010). Diurnal variations of global thunderstorms and electrified shower clouds and their contribution to the global electrical circuit. Journal of the atmospheric sciences, 67(2), 309-323. https://doi.org/10.1175/2009JAS3248.1 Liu, C., & Heckman, S. (2011). Using total lightning data in severe storm prediction: Global case study analysis from north America, Brazil and Australia. In 2011 International Symposium on Lightning Protection (pp. 20-24). IEEE. https://ieeexplore.ieee.org/document/6088433/ Lyu, F., Cummer, S. A., Krehbiel, P. R., Rison, W., Bruning, E. C., & Rutledge, S. A. (2021). A distinct class of high peak‐current lightning pulses over mountainous terrain in thunderstorms. Geophysical Research Letters, 48(14), e2021GL094153. https://doi.org/10.1029/2021GL094153 Mallick, S., Rakov, V. A., Hill, J. D., Ngin, T., Gamerota, W. R., Pilkey, J. T., ... & Liu, C. (2015). Performance characteristics of the ENTLN evaluated using rocket-triggered lightning data. Electric power systems research, 118, 15-28. https://doi.org/10.1016/j.epsr.2014.06.007 Peterson, M. (2023). WWLLN energetic lightning events are different from optical superbolts. Geophysical Research Letters, 50, e2023GL104074. https://doi.org/10.1029/2023GL104074 Price, C. (2009). Thunderstorms, Lightning and Climate Change. In: Betz, H.D., Schumann, U., Laroche, P. (eds) Lightning: Principles, Instruments and Applications. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9079-0_24 Said, R. K., Cohen, M. B., & Inan, U. S. (2013). Highly intense lightning over the oceans: Estimated peak currents from global GLD360 observations. Journal of Geophysical Research: Atmospheres, 118(13), 6905-6915. https://doi.org/10.1002/jgrd.50508 Smorgonskii, A., Rubinstein, M., & Rachidi, F. (2018, March). Extreme Values of Lightning Parameters. In Proc. 25th International Lightning Detection Conference & 7th International Lightning Meteorology Conference, March (pp. 12-15). Turman, B. N. (1977). Detection of lightning superbolts. Journal of Geophysical Research, 82(18), 2566-2568. https://doi.org/10.1029/JC082i018p02566 Williams, E., Rothkin, K., Stevenson, D., & Boccippio, D. (2000). Global lightning variations caused by changes in thunderstorm flash rate and by changes in the number of thunderstorms. Journal of Applied Meteorology, 39(12), 2223-2230. https://doi.org/10.1175/1520-0450(2001)040%3C2223:GLVCBC%3E2.0.CO;2 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7415246","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":514422333,"identity":"a8ec6871-a231-4429-8abe-269c3e541082","order_by":0,"name":"Mustafa Asfur","email":"","orcid":"","institution":"Ruppin Academic Center","correspondingAuthor":false,"prefix":"","firstName":"Mustafa","middleName":"","lastName":"Asfur","suffix":""},{"id":514422334,"identity":"6c09a371-0c7a-46ee-a9e4-e3b65f4db0da","order_by":1,"name":"Jacob Silverman","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYBACxgYGBmYGBgk5ZLHGA0RosTBGEcOrBQSAWioSG5BF8Gphbj/88HHBH4n0fvbDBz8XMNjkyzsw47eFsSfN2Hhmm0TuzJ60ZOkZDGmWGw8QcBhjQw6bNG+DRO6GGzwG0jwMhw0MGwhp6X/DJs0DdJjBDf7Pv4nTMgNoCw+bRILBDR42sC3yhEKMccYzsF8MgX4xs+YxSDMwYCagxbA/GRRidfL87Icf3+apsDGQb29/+ACvlgYUrgEQHcanHgjkMUUaMFWNglEwCkbByAYAEFNE0g7Xvw0AAAAASUVORK5CYII=","orcid":"","institution":"National Institute of Oceanography (IOLR)","correspondingAuthor":true,"prefix":"","firstName":"Jacob","middleName":"","lastName":"Silverman","suffix":""}],"badges":[],"createdAt":"2025-08-20 08:38:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7415246/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7415246/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-29669-w","type":"published","date":"2025-11-23T15:56:59+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":91606010,"identity":"7dd09616-9986-4de3-a18c-e6e2f16e8160","added_by":"auto","created_at":"2025-09-18 09:23:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":102072,"visible":true,"origin":"","legend":"\u003cp\u003eMonthly (a) and daily (b) distributions of Lightning Superbolts (SBs) with energies greater than 1 MJ, based on the Holzworth \u003cem\u003eet al.\u003c/em\u003e (2019) WWLLN dataset for the period 2010-2018. In panel a, the orange and blue bars indicate the monthly distribution of SBs in the northern and southern hemispheres (NH and SH), respectively. The time axis in panel (b) is in UT.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415246/v1/80d33b4c98ee65147d2b4584.jpg"},{"id":91606016,"identity":"4c160a7b-4a55-4c8c-9f6a-84f06cdb9d40","added_by":"auto","created_at":"2025-09-18 09:23:06","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":185659,"visible":true,"origin":"","legend":"\u003cp\u003eThe global average CGs density (# km\u003csup\u003e-2\u003c/sup\u003e·yr\u003csup\u003e-1\u003c/sup\u003e) distribution for all CG events with Ip\u0026gt;30 kA that occurred over the period 2018-2021.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415246/v1/180cc43270ef499677450411.jpg"},{"id":91606013,"identity":"2aa13a51-bbcf-40d7-b54c-fbe8a4b80d5a","added_by":"auto","created_at":"2025-09-18 09:23:06","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":137688,"visible":true,"origin":"","legend":"\u003cp\u003eThe proportions of CGs with Ip \u0026gt; 30 kA out of the total number of CGs recorded over the period 2018-2021 globally (blue line) with Ip \u0026gt; 2 kA, over the continents (green line) and over the oceans (orange line). The black dashed curve represents the ratio of CGs with Ip \u0026gt; 30 kA and above over the oceans (sea) and continents (land). The black and red dashed lines indicate the proposed proportions of SBs out of the total number of CGs with Ip \u0026gt; 2 kA.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415246/v1/dc819204efb310313f0eb071.jpg"},{"id":91606017,"identity":"227c6cc3-a350-430b-8df9-1031e3ed7efb","added_by":"auto","created_at":"2025-09-18 09:23:06","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":139147,"visible":true,"origin":"","legend":"\u003cp\u003eDiel distributions of land (empty markers) and sea (full markers) normalized frequencies of high Ip cloud-to-ground strokes above different peak current thresholds (Ip\u0026gt;30, \u0026gt;50, \u0026gt;100 and \u0026gt;200 kA, left hand Y axis) compared the normalized fair-weather atmospheric electric field Carnegie Curve (Blue dashed line, right hand Y axis), that was calculated according to Harrison (2020). The time axis in in UT.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415246/v1/7c2ead7cd691d5019972349b.jpg"},{"id":91608919,"identity":"1be6651b-61b6-4fcf-b5ac-d33621546157","added_by":"auto","created_at":"2025-09-18 09:39:06","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":111363,"visible":true,"origin":"","legend":"\u003cp\u003eHourly distributions of ratios of the cumulative frequencies above the Ip thresholds between 30 and 1000 kA (every 2 kA) for CGs over the oceans and the land measured globally by ENTLN during the period 2018-23. The dashed white line represents the fair-weather atmospheric electric field strength calculated according to Harrison (2020) and adjusted to the Ip threshold axis scale.\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7415246/v1/d590f80350cae2eabf96b50f.jpg"},{"id":96649977,"identity":"290ccd76-dbc9-4583-87ec-25bfd6218237","added_by":"auto","created_at":"2025-11-24 16:02:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1064546,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7415246/v1/4eeae24e-7c6f-4fc4-8602-b9f0bbe5fb75.pdf"},{"id":91609963,"identity":"b351c04f-dae9-48ff-ab89-19ad2d240229","added_by":"auto","created_at":"2025-09-18 09:47:06","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":167370,"visible":true,"origin":"","legend":"","description":"","filename":"AsfurandSilvermanSOMSREPAug2025.docx","url":"https://assets-eu.researchsquare.com/files/rs-7415246/v1/9a9459396e8722964bf40da7.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Reevaluating the Global and Temporal Distributions of Lightning Superbolts: Insights from ENTLN Data (2018–2021)","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn an analysis of cloud to ground lightning observations using a global VHF antenna network (GLD360) it was determined that the geometric mean peak current (Ip) of negative polarity cloud to ground lightning strikes (CGs) for the first return stroke was ~\u0026thinsp;10\u0026ndash;30 kA over the continents (Said et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In contrast, the geometric mean of CGs Ip measured over the oceans in Said et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) varied in the range of ~\u0026thinsp;25\u0026ndash;45 kA. These energy categories of lightning strikes represent 95% of all CGs measured over the land and oceans globally during a one-year period (\u003cem\u003eOp. Cit.\u003c/em\u003e). The spatial-temporal global distribution of total lightning (CG\u0026thinsp;+\u0026thinsp;intra cloud) in general has been previously determined based on satellite observations, where lightning occur most frequently over the land, during summertime in the northern temperate zone (Christian et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), while over the oceans, lightning occurs much less frequently, by a factor of ~\u0026thinsp;10 (\u003cem\u003eOp. Cit.\u003c/em\u003e).\u003c/p\u003e\u003cp\u003ePrevious studies, most notably Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) showed based on the World-Wide Lightning Location Network (WWLLN) that high energy CGs (\u0026gt;\u0026thinsp;1 MJ) detected by the Very Low Frequency Time Of Arrival (VLF-TOA) network, also known as Super Bolts (SBs), which represent substantially less than 1% of the total CGs included in their dataset, occur predominantly over the oceans (\u0026gt;\u0026thinsp;90%). This is consistent with Hutchins et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), who showed that the ratio of lightning strokes observed by WWLLN, over the oceans and continents increases with increasing lightning stroke energy above 3000 J, where this ratio reaches a plateau value of ~\u0026thinsp;2 for lightning strokes with energies in the range of 10\u003csup\u003e4\u003c/sup\u003e-10\u003csup\u003e6\u003c/sup\u003e J. It is interesting to note that the analysis of Hutchins et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) excluded lightning flashes with energies above 10\u003csup\u003e6\u003c/sup\u003e J, which were the focus of the Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) analysis.\u003c/p\u003e\u003cp\u003eHolzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) defined two energy classes for SBs collected between 2010\u0026ndash;2018, where the lower energy class included all SBs with energy\u0026thinsp;\u0026gt;\u0026thinsp;1MJ and the higher energy class included all SBs with energy\u0026thinsp;\u0026gt;\u0026thinsp;2MJ. Based on this classification Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), identified a total of 8171 SBs throughout the study period with energies greater than 1 MJ, out of which 1719 events had energies greater than 2 MJ. These observations comprised 0.001% of all CGs recorded by WWLLN throughout the measuring period, and have energies three orders of magnitude above the mean value for a cloud-to-ground stroke (1000 J). According to the conversion equation of Hutchins et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), the mean radiated stroke energy in the Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) dataset is equivalent to a peak current of 35 kA assuming a triggering window of 0.00133 ms. This mean value is substantially higher than the detection threshold (2 kA) of VLF-TOA lightning detection systems proposed by Krider et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The cutoff energy for SBs used in Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) is 10\u003csup\u003e6\u003c/sup\u003e J, which is equivalent to ~\u0026thinsp;3000 kA according to the conversion equation of Hutchins et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and assuming a triggering window of 0.00133 ms. This Ip is extremely high, however, it is well known from basic electrodynamic principles that the lightning duration increases with the power of the lightning bolt and therefore the calculated Ip will decrease according to the Huchins \u003cem\u003eet al.\u003c/em\u003e (2013) equation and therefore assuming a two order of magnitude increase in the triggering window duration (0.133 ms), the cutoff Ip decreases to ~\u0026thinsp;180 kA, which seems to be a much more reasonable value.\u003c/p\u003e\u003cp\u003eNonetheless, according to the classification and global distribution of Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), most of the SBs occurred in the northern hemisphere (72%) during the wintertime (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). Furthermore, it is also possible to identify global hotspots for SBs (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e in Holzworth et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), including the Mediterranean Sea region (~\u0026thinsp;24% of all SBs), the North Sea region (~\u0026thinsp;16%), the Chilean high plateau (~\u0026thinsp;10%), and off the coast of South Africa (~\u0026thinsp;4%). Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), also noted that most (86%) of the SBs occurred during the solar maximum (2013-15) and suggested that this correlation may be potentially causal. Finally, while lower energy CGs in general are most prevalent during the late afternoon to early evening hours (\u003cem\u003ee.g.\u003c/em\u003e, Williams et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Price, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), according to the Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) dataset, SBs exhibit a daily cycle with a maximum frequency after midnight until 0600 and a minimum frequency at midday (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). This daily variation is in opposite phase to the fair-weather atmospheric electric field strength variation, also known as the Carnegie Curve.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTurman (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1977\u003c/span\u003e), first characterized SBs based on optical measurements from the Vela satellites and land based worldwide VLF monitoring network measurements (Freeman, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1974\u003c/span\u003e). Turman (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1977\u003c/span\u003e) considered the upper 2% of the optical spectrum from the Vela measurements of optical power and showed that the corresponding energy of VLF RF sferics measurements (Freeman, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1974\u003c/span\u003e) were significantly and positively correlated (n\u0026thinsp;=\u0026thinsp;17, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.43, p\u0026thinsp;=\u0026thinsp;0.0038; correlation input data from Turman \u003cem\u003eet al.\u003c/em\u003e (1977)). Thus, it was determined that the peak optical power of SBs is greater than 10 GW or 100 MJ in energy units of RF sferics that were output by the VLF system. In a later study, Kirkland (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) determined the optical power threshold for SBs to be \u0026gt;\u0026thinsp;100 GW, an order of magnitude higher than the Turman threshold. Finally, in a recent study, a comparison was conducted between satellite optical power of lightning flashes and corresponding energy levels of CGs measured by WWLLN (Peterson, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). It was shown that lightning bolts with an optical intensity of \u0026gt;\u0026thinsp;100 GW, qualifying them as optical SBs (Kirkland, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1999\u003c/span\u003e), had energies 2\u0026ndash;3 orders of magnitude lower than the 10\u003csup\u003e6\u003c/sup\u003e J threshold defined by Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Together with the discrepancies between the classification of SBs by Turman (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1977\u003c/span\u003e), Kirkland (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1999\u003c/span\u003e) and Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) in terms of frequency (2%, 0.46% and 0.001%, respectively) and their energy (10 GW (100 MJ), 100 GW (1GJ) and 1MJ, respectively) it is somewhat difficult to determine a cutoff energy or Ip for SBs based on state-of-the-art VLF Ip measurements (\u003cem\u003ee.g.\u003c/em\u003e, ENTLN). For example, in order to discuss the land-ocean differences, frequencies, spatial distributions and conditions under which SBs occur, it is imperative to provide a more robust SB Ip threshold for these state-of-the-art systems.\u003c/p\u003e\u003cp\u003eAccording to Cooray and Rakov (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), assuming a maximum background electric field below thunderclouds of 150 kV/m, the theoretical upper limit for CGs peak current is 450\u0026ndash;500 kA in the tropics and 300 kA in the temperate zones. Nonetheless, CGs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;500 kA and even \u0026gt;\u0026thinsp;1000 kA over the land have been measured and reported with VLF-TOA systems (\u003cem\u003ee.g.\u003c/em\u003e, Lyu et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this study, we examined the Earth Networks Total Lightning Network CG data from the period 2018\u0026ndash;2021 to determine the cutoff Ip for SBs over the land and the oceans, which includes the upper 1% of all CGs included in the dataset. Where, according to Asfur et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), it is understood that the conductivity of the ground influences to a great extent the intensity of the lightning discharge. In addition, we will determine the annual, daily and global distributions of these SBs and their ocean-land ratios.\u003c/p\u003e"},{"header":"Methods and Analysis Protocols","content":"\u003cp\u003eEarth Networks Total Lightning Network (ENTLN) is comprised of over 1800 lightning sensors deployed globally (Liu \u0026amp; Heckman, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The ENTLN is capable of observing lightning return strokes or multiple strokes (Mallick et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In this study, CG data were obtained and analyzed for the period January 2018 until March 2021 without differentiating between the first and following return strokes (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.earthnetworks.com/product/lightning-data/\u003c/span\u003e\u003cspan address=\"https://www.earthnetworks.com/product/lightning-data/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The entire dataset (Ip\u0026thinsp;=\u0026thinsp;0-1000 kA) included 3.78\u0026middot;10\u003csup\u003e9\u003c/sup\u003e CG events with positive and negative polarities. Out of this dataset, CG strokes with Ip\u0026thinsp;\u0026ge;\u0026thinsp;30 kA, which is equivalent to 550 J, according to the Hutchins et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) conversion equation, were extracted for further analysis. Altogether, the ENTLN subset (\u0026gt;\u0026thinsp;30 kA) constitutes\u0026thinsp;~\u0026thinsp;0.8% of all CGs in the original dataset. The subset was binned into 2 kA bins for positive and negative polarities separately as well as separated for land and sea. Based on the distribution with PC of percent of the total we tried to determine a PC threshold for SBs over the continents and the oceans. Finally, the subsets of SBs over the continents and oceans were sorted by hour to determine the diel distribution of continental and oceanic SBs.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe global lightning density distribution (per 0.25\u0026deg;X0.25\u0026deg;) for all events with Ip\u0026thinsp;\u0026gt;\u0026thinsp;30 kA (negative and positive polarities) that occurred during the study period, indicate significantly higher densities of high peak-current strokes over the land than over the oceans (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), with the highest densities over the continents in the southern hemisphere. The \"Hotspots\" of high continental lightning densities are apparent over the Andes region, Northern Columbia and Venezuela (Lake Maracaibo) in south America, in South Africa, the Maritime Continent in Southeast Asia and Northern Australia. This \u0026ldquo;hotspot\u0026rdquo; distribution is similar to the one described by Albrecht et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) that was based on optical intensity records. Over the oceans, CGs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;30 kA is relatively equally distributed (mostly lower than 1000 strikes per 0.25\u0026deg;X0.25\u0026deg;) between the latitude of 60\u0026deg;S and 60\u0026deg;N, with empty patches in the south Atlantic and Pacific oceans extending out from Western Africa and South America, respectively. There is also a sporadically bare patch of ocean extending from North America out into the Pacific Ocean and a bare zonal band along the equator in the Pacific Ocean. It should be noted that the regions bare of CGs in the southern hemisphere in the Atlantic and Pacific oceans as well as along the equatorial pacific correspond to upwelling regions along the continents and along the equator. Despite the relatively low densities in the oceans, it is possible to identify oceanic regions with relatively higher densities (1000\u0026ndash;3000 strikes per 0.25\u0026deg;X0.25\u0026deg;) in the Mediterranean Sea, Gulf of Mexico, Arabian Sea, the regions across from Liberia and Cameroon in the Atlantic Ocean, in the region off the coasts of Mexico and California in the Pacific Ocean and others. It is interesting to note that in the region of the North Sea and English Channel the density of CGs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;30 kA is very low and in large areas even bare. This finding is contradictory to the distributions of SBs in the North Sea and English Channel during the period 2010\u0026ndash;2018, presented in Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAs stated above, the relative proportion of CGs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;30 kA from the total analyzed dataset is ~\u0026thinsp;3.3%, while continental CGs comprises 2.8% and oceanic CGs is 4.1% of the total number of CGs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;2 kA. In Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, the proportion of lightning events out of the total CGs is presented as a function of an increasing Ip threshold in a log-linear plot. According to Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, it is evident that the proportion of all CGs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;50 kA is strongly influenced by the proportion of the total occurring over the oceans and the peak sea to land ratio actually has two distinct peaks with values of 15 and 13 at Ip\u0026thinsp;\u0026gt;\u0026thinsp;120 and 150, respectively. In Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec, the proportion of CGs decreases with increasing Ip along a sigmoidal curve, dropping very quickly to 0.01% at ~\u0026thinsp;500 kA and continues to decrease slowly to 0.0006% at 900 kA and drops quickly beyond to 0.00001% at 1000 kA. It should be noted that there is a high degree of skepticism regarding peak currents greater than the upper theoretical limits of Cooray and Rakov (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) (300\u0026ndash;500 kA). Nonetheless, it is interesting to note that the percentage at 500 kA threshold, which is the highest theoretical limit for lightning bolts in the tropics according to Cooray \u0026amp; Rakov (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) is 0.001%, \u003cem\u003ei.e.\u003c/em\u003e, 1 out 10\u003csup\u003e5\u003c/sup\u003e lightning bolts are SBs.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe daily distribution of CGs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;30, 50, 100 and 200 kA, yields different distributions for the land and the sea (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The graph illustrates how the frequency of lightning strikes varies throughout the day over land and sea above different current thresholds, compared to the fair-weather Carnegie curve, which was calculated according to Harrison (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Generally, the normalized frequency of high Ip lightning strikes over land exhibit a notable increase during the afternoon and evening hours, with a marked decrease in the early morning and late night. In contrast the normalized frequency of high Ip lightning strikes over the sea exhibits peak values during the late afternoon and early evening hours and decrease to minimum values during the early morning hours. Overall, the sea distributions correspond well with the normalized fair-weather Carnegie curve, while the land distribution are out of phase.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion and Conclusions","content":"\u003cp\u003ePrevious studies, based on optical and VLF observations, determined that lightning superbolts (SBs) occur predominantly over the oceans. Turman (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1977\u003c/span\u003e) based his conclusion on 3 years of Vela optical observations (1972-75), which consisted of thousands of flashes (as reported). Where, 1% of the flashes were categorized as SBs that occurred predominantly over the north west Pacific near the coast of Japan. Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) based his conclusion on 10 years of WWLLN data, which recorded millions of flashes by ~\u0026thinsp;70 antennas distributed globally. Where, 0.001% of the CGs were categorized as SBs, out of which\u0026thinsp;\u0026gt;\u0026thinsp;90% occurred over the oceans, specifically in regions including, the Mediterranean Sea, the Northern Sea, the Indian and Atlantic oceans along the equator, and along the 45\u0026deg;N and 45\u0026deg;S parallels across the Pacific and Atlantic oceans. In this study, which is based on the ENTLN data consisting of ~\u0026thinsp;10\u003csup\u003e9\u003c/sup\u003e CGs, collected by ~\u0026thinsp;1200 antennas distributed globally, during the period 2018\u0026ndash;2021, the proportion of high peak current CGs over the oceans compared to land was greater than 1 starting at Ip\u0026thinsp;\u0026gt;\u0026thinsp;50 kA and no more than ~\u0026thinsp;15 for Ip\u0026thinsp;\u0026gt;\u0026thinsp;120 kA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). For Ip\u0026thinsp;\u0026gt;\u0026thinsp;200 kA, the peak sea to land ratio of 2.4 occurs at Ip\u0026thinsp;\u0026gt;\u0026thinsp;380 kA and decreases to a relatively constant ratio of 1.2 from Ip\u0026thinsp;\u0026gt;\u0026thinsp;550 kA. These findings are inconsistent with the findings of Turman (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1977\u003c/span\u003e) and Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), with respect to the sea-land cloud-to-ground stroke ratios. However, it should be noted that within the threshold range of 90\u0026ndash;180 kA, the average sea to land ratio is ~\u0026thinsp;9, i.e., 90% of the CGs in this threshold range occur over the oceans, similar to the result of Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe theoretical upper thresholds for peak current values in cloud-to-ground strokes in the tropics and temperate zones according to Cooray and Rakov (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) are 500 and 300 kA, respectively. Thus, the proportions of strong strokes with peak currents in the above ranges of the total based on the ENTLN data in the present study varies in the range 0.0003\u0026ndash;0.003%, where the sea-land ratio varies in the range\u0026thinsp;~\u0026thinsp;1.5\u0026ndash;2.4 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). It appears that the occurrence of CGs with peak currents in the range 50\u0026ndash;190 kA is substantially more frequent over sea than land, suggesting that these high peak current discharges over the oceans are more the rule than the exception. Thus, if SBs are characterized as extremely rare events (0.0001%) according to Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), then according to this dataset, the threshold for SBs, should be set higher than 700 kA, where the sea-land ratio is relatively constant with increasing Ip at ~\u0026thinsp;1.5. However, despite the fact that Ip\u0026thinsp;\u0026gt;\u0026thinsp;500 kA have been previously measured by VLF-TOA systems and reported in the scientific literature (\u003cem\u003ee.g.\u003c/em\u003e, Smorgonskii et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), it is generally accepted that these extreme values are not real and most likely measurement artifacts. Nonetheless, it should be noted that the theoretical upper limits of Ip for CGs determined by Cooray \u0026amp; Rakov (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) were calculated under the assumptions that Ip is limited by the maximum measured atmospheric breakdown potential of 150 kV/m and the mean lightning discharge duration of 100 \u0026micro;s following the reanalysis of measurement from Cooray et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). These values appear to be relatively arbitrary considering the large variation of observed discharge durations (\u003cem\u003ee.g.\u003c/em\u003e, Smorgonskii et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2018\u003c/span\u003e\u0026ndash;30 \u0026micro;s \u0026ndash; 1928 ms) and observed values of electric field strength, which do not even attain the experimental breakdown potential for dry air of 3 MV/m (\u003cem\u003ee.g.\u003c/em\u003e, Hogg et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eConsidering the continental subset of the Ip\u0026thinsp;\u0026gt;\u0026thinsp;30 kA, the relative proportion of continental CGs out of the total continental CGs (0-1000 kA) is 2.8% (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Similarly, the relative proportion of ocean CGs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;30 kA out of the total oceanic CGs (0-1000 kA) is 4.1%. Where, it should be noted that most of the CGs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;30 kA occurred in the latitudinal range of 40\u0026deg;S to 40\u0026deg;N (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). It is interesting to note that the Ip for 0.01% of CGs over the continents is 165 kA, while over the oceans it is 260 kA. Thus, assuming that 0.01% of all CGs can be characterized as SBs, it is apparent that the Ip threshold over the oceans is substantially greater than the threshold over the continents. This finding is consistent with the findings of Said et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and the conclusions of Asfur et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), who suggested that the lightning intensity is strongly influenced by the conductivity of the receiving surface (solid ground \u0026minus;\u0026thinsp;0\u0026ndash;10 mS/cm compared to seawater \u0026ndash; 50\u0026ndash;60 mS/cm). Finally, the sea to land ratio of CGs increases from a minimum value of ~\u0026thinsp;0.8 at Ip\u0026thinsp;\u0026gt;\u0026thinsp;30 kA to a maximum value of ~\u0026thinsp;15 at Ip\u0026thinsp;\u0026gt;\u0026thinsp;1 kA (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). After the maxima, the ratio drops rapidly to ~\u0026thinsp;1.9 at ~\u0026thinsp;190 kA and remains relatively steady thereafter.\u003c/p\u003e\u003cp\u003eThe relative contribution of oceanic and continental lightning activity to the diel variation in the fair-weather electric field, the Carnegie curve, has been previously investigated by Liu et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In their study, it was shown that the diel variations in the electrical activity of clouds over both land and oceans in the latitudinal range of 35\u0026deg;S to 35\u0026deg;N, determined from TRMM rainfall reflectance measurements, were in phase with the Carnegie curve. In this study, the contribution of CGs over the oceans with 80\u0026thinsp;\u0026lt;\u0026thinsp;Ip\u0026thinsp;\u0026lt;\u0026thinsp;150 kA relative to CGs over the land in the same Ip range is apparently in phase with the Carnegie curve during the afternoon, but out of phase throughout the night and early morning hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). This result suggests that that the relative contribution of SBs over the ocean to the Carnegie curve in the afternoon and early evening is significant, while the relative contributions during the nighttime is insignificant. However, it can be inferred from Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e that the combined diel distributions of land and ocean CG frequencies is in phase with the Carnegie curve, where the highest correlation coefficient is observed for SBs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;50 kA (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.84) (Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn conclusion, the analysis of this global dataset shows that high intensity CGs with Ip in the range of 125\u0026ndash;155 kA observed over the period 2018-21, occur 13\u0026ndash;15 times more often over the oceans relative to the continents. Above this range the sea to land ratio decreases to an average value of 1.6 for Ip\u0026thinsp;\u0026gt;\u0026thinsp;180 kA, which is somewhat lower than the theoretical upper limit for Ip of 300 kA, estimated for temperate latitudes (Cooray \u0026amp; Rakov, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Where, the recorded CGs with Ip\u0026thinsp;\u0026gt;\u0026thinsp;500 kA, which is the upper theoretical limit of Ip estimated for the tropics, represents ca. 0.0003% of the total lightning. This percentage is an order of magnitude smaller than the proportion determined by Holzworth et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) for SBs that predominantly occur over the oceans. Finally, the diel distributions of high intensity CGs indicate that they occur predominantly over the oceans throughout the entire day and are in phase with the fair-weather atmospheric electric field strength throughout the afternoon and early hours, but are in opposite phase during the nighttime and early morning hours. However, the combined diel distributions of SBs (land and ocean) exhibit a strong positive correlation with the phase of the Carnegie curve.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements and Funding Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author gratefully acknowledges the Earth Networks Total Lightning Network (ENTLN) for providing access to lightning data used in this study. We sincerely appreciate permission to use the data. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration section\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMustafa Asfur: Conceptualization, data curation, formal analysis, methodology, writing\u0026mdash;original draft, visualization.\u003c/p\u003e\n\u003cp\u003eJacob Silverman: Conceptualization, data curation, formal analysis, methodology, writing\u0026mdash;original draft, visualization.\u003c/p\u003e\n\u003cp\u003eBoth authors contributed to manuscript revision and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data presented are based on raw data of lightning measurements provided by ENTLN (https://ghrc.nsstc.nasa.gov/home/content/earth-networks-total- lightning-network-entln-global-lightning-network), which may be provided directly from this vendor.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlbrecht, R. I., Goodman, S. J., Buechler, D. E., Blakeslee, R. J., \u0026amp; Christian, H. J. (2016). Where are the lightning hotspots on Earth? Bulletin of the American Meteorological Society, 97(11), 2051-2068. https://doi.org/10.1175/BAMS-D-14-00193.1 \u003c/li\u003e\n\u003cli\u003eAsfur, M., Price, C., Silverman, J., \u0026amp; Wishkerman, A. (2020). Why is lightning more intense over the oceans? Journal of Atmospheric and Solar-Terrestrial Physics, 202, 105259. https://doi.org/10.1016/j.jastp.2020.105259 \u003c/li\u003e\n\u003cli\u003eChristian, H. J., Blakeslee, R. J., Boccippio, D. J., Boeck, W. L., Buechler, D. E., Driscoll, K. T., ... \u0026amp; Stewart, M. F. (2003). Global frequency and distribution of lightning as observed from space by the Optical Transient Detector. Journal of Geophysical Research: Atmospheres, 108(D1), ACL-4. https://doi.org/10.1029/2002JD002347 \u003c/li\u003e\n\u003cli\u003eCooray, V., Rakov, V., \u0026amp; Theethayi, N. (2007). The lightning striking distance\u0026mdash;Revisited. Journal of Electrostatics, 65(5-6), 296-306. https://doi.org/10.1016/j.elstat.2006.09.008 \u003c/li\u003e\n\u003cli\u003eCooray, V., \u0026amp; Rakov, V. (2012). On the upper and lower limits of peak current of first return strokes in negative lightning flashes. Atmospheric research, 117, 12-17. https://doi.org/10.1016/j.atmosres.2011.06.002\u003c/li\u003e\n\u003cli\u003eFreeman, W. B. (1974). The distribution of thunderstorm and lightning parameters over the eastern hemisphere for 1972 (Doctoral dissertation, Texas A\u0026amp;M University). https://hdl.handle.net/1969.1/ETD-TAMU-1974-THESIS-F855\u003c/li\u003e\n\u003cli\u003eHarrison, R. G. (2020). Behind the curve: a comparison of historical sources for the Carnegie curve of the global atmospheric electric circuit. History of Geo-and Space Sciences, 11(2), 207-213. https://doi.org/10.5194/hgss-11-207-2020\u003c/li\u003e\n\u003cli\u003eHogg, M. G., Timoshkin, I. V., Macgregor, S. J., Wilson, M. P., Given, M. J., \u0026amp; Wang, T. (2013, June). Electrical breakdown of short non-uniform air gaps. In 2013 19th IEEE Pulsed Power Conference (PPC) (pp. 1-4). IEEE. https://doi.org/10.1109/PPC.2013.6627482\u003c/li\u003e\n\u003cli\u003eHolzworth, R. H., McCarthy, M.P., Brundell, J. B., Jacobson, A. R., \u0026amp; Rodger, C. J. (2019). Global Distribution of Superbolts. J. Geophys. Res. Atmos. 124 (17-18), 9996-10005. https://doi.org/10.1029/2019JD030975\u003c/li\u003e\n\u003cli\u003eHutchins, M. L., Holzworth, R. H., Virts, K. S., Wallace, J. M., \u0026amp; Heckman, S. (2013). Radiated VLF energy differences of land and oceanic lightning. Geophysical Research Letters, 40(10), 2390-2394. https://doi.org/10.1002/grl.50406\u003c/li\u003e\n\u003cli\u003eKirkland, M. W. (1999). An examination of superbolt‐class lightning events observed by the FORTE satellite. Los Alamos National Laboratory, Atmospheric Sciences Group, New Mexico. https://citeseerx.ist.psu.edu/document?repid=rep1\u0026amp;type=pdf\u0026amp;doi=114dac189f035ccdce46c7d67e35b0c1504874d3 \u003c/li\u003e\n\u003cli\u003eKrider, E. P., Cummins, K. L., Biagi, C. J., Fleenor, S. A., \u0026amp; Wilson, J. G. (2010, September). Small negative strokes in cloud-to-ground lightning flashes. In 2010 30th International Conference on Lightning Protection (ICLP) (pp. 1-3). IEEE. https://doi.org/10.1109/ICLP.2010.7845966\u003c/li\u003e\n\u003cli\u003eLiu, C., Williams, E. R., Zipser, E. J., \u0026amp; Burns, G. (2010). Diurnal variations of global thunderstorms and electrified shower clouds and their contribution to the global electrical circuit. Journal of the atmospheric sciences, 67(2), 309-323. https://doi.org/10.1175/2009JAS3248.1 \u003c/li\u003e\n\u003cli\u003eLiu, C., \u0026amp; Heckman, S. (2011). Using total lightning data in severe storm prediction: Global case study analysis from north America, Brazil and Australia. In 2011 International Symposium on Lightning Protection (pp. 20-24). IEEE. https://ieeexplore.ieee.org/document/6088433/ \u003c/li\u003e\n\u003cli\u003eLyu, F., Cummer, S. A., Krehbiel, P. R., Rison, W., Bruning, E. C., \u0026amp; Rutledge, S. A. (2021). A distinct class of high peak‐current lightning pulses over mountainous terrain in thunderstorms. Geophysical Research Letters, 48(14), e2021GL094153. https://doi.org/10.1029/2021GL094153 \u003c/li\u003e\n\u003cli\u003eMallick, S., Rakov, V. A., Hill, J. D., Ngin, T., Gamerota, W. R., Pilkey, J. T., ... \u0026amp; Liu, C. (2015). Performance characteristics of the ENTLN evaluated using rocket-triggered lightning data. Electric power systems research, 118, 15-28. https://doi.org/10.1016/j.epsr.2014.06.007 \u003c/li\u003e\n\u003cli\u003ePeterson, M. (2023). WWLLN energetic lightning events are different from optical superbolts. Geophysical Research Letters, 50, e2023GL104074. https://doi.org/10.1029/2023GL104074 \u003c/li\u003e\n\u003cli\u003ePrice, C. (2009). Thunderstorms, Lightning and Climate Change. In: Betz, H.D., Schumann, U., Laroche, P. (eds) Lightning: Principles, Instruments and Applications. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-9079-0_24 \u003c/li\u003e\n\u003cli\u003eSaid, R. K., Cohen, M. B., \u0026amp; Inan, U. S. (2013). Highly intense lightning over the oceans: Estimated peak currents from global GLD360 observations. Journal of Geophysical Research: Atmospheres, 118(13), 6905-6915. https://doi.org/10.1002/jgrd.50508 \u003c/li\u003e\n\u003cli\u003eSmorgonskii, A., Rubinstein, M., \u0026amp; Rachidi, F. (2018, March). Extreme Values of Lightning Parameters. In Proc. 25th International Lightning Detection Conference \u0026amp; 7th International Lightning Meteorology Conference, March (pp. 12-15).\u003c/li\u003e\n\u003cli\u003eTurman, B. N. (1977). Detection of lightning superbolts. Journal of Geophysical Research, 82(18), 2566-2568. https://doi.org/10.1029/JC082i018p02566 \u003c/li\u003e\n\u003cli\u003eWilliams, E., Rothkin, K., Stevenson, D., \u0026amp; Boccippio, D. (2000). Global lightning variations caused by changes in thunderstorm flash rate and by changes in the number of thunderstorms. Journal of Applied Meteorology, 39(12), 2223-2230. https://doi.org/10.1175/1520-0450(2001)040%3C2223:GLVCBC%3E2.0.CO;2 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7415246/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7415246/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLightning superbolts (SBs), defined as cloud-to-ground strokes with extraordinarily high peak currents (Ip\u0026rsquo;s), represent a rare and extreme category of lightning events (\u0026lt;\u0026thinsp;1% of the total lightning). This study reevaluates the global and temporal distributions of SBs using data from the Earth Networks Total Lightning Network (ENTLN) collected between 2018 and 2021. By focusing on strokes with Ip\u0026thinsp;\u0026ge;\u0026thinsp;30 kA (HIp), which constitute approximately 0.8% of all recorded events, the study analyzes their spatial distribution, diel patterns, and land-ocean ratios and reevaluates the Ip cutoff for SBs.\u003c/p\u003e\u003cp\u003eThe results indicate that HIp strokes are more densely concentrated over land than oceans, with continental hotspots identified in regions such as the Andes, Lake Maracaibo, the tall grass prairies of the United States and Southeast Asia. Conversely, oceanic HIp are relatively evenly distributed across latitudes but exhibit localized density increases in areas such as the Mediterranean Sea, Gulf of Mexico, Maritime Indonesia and of the western coasts of Africa and Central America. The study also finds that HIp with Ip\u0026thinsp;\u0026gt;\u0026thinsp;50 kA exhibit a sea-to-land ratio greater than one, peaking at a ratio of ~\u0026thinsp;15 for Ip\u0026thinsp;\u0026gt;\u0026thinsp;120 kA before declining at higher Ip thresholds. Finally, temporal analyses reveal distinct diel patterns for HIp over land and sea, with oceanic distributions of the total lightning closely mirroring the Carnegie Curve's fair-weather atmospheric electric field diel variation.\u003c/p\u003e","manuscriptTitle":"Reevaluating the Global and Temporal Distributions of Lightning Superbolts: Insights from ENTLN Data (2018–2021)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-18 09:23:01","doi":"10.21203/rs.3.rs-7415246/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-14T10:51:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-13T23:35:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-01T02:45:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"59749283574909020584007456264511004618","date":"2025-09-22T11:51:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172662996435978303340936659440831459436","date":"2025-09-22T10:31:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"245874840460665207514149410736863627044","date":"2025-09-22T04:58:31+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-11T05:49:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-11T05:29:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-03T21:32:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-02T07:57:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-09-02T07:53:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"439a652a-0d65-4a7e-9031-6f0137243569","owner":[],"postedDate":"September 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":54654587,"name":"Earth and environmental sciences/Climate sciences"},{"id":54654588,"name":"Earth and environmental sciences/Environmental sciences"},{"id":54654589,"name":"Earth and environmental sciences/Ocean sciences"}],"tags":[],"updatedAt":"2025-11-24T15:59:47+00:00","versionOfRecord":{"articleIdentity":"rs-7415246","link":"https://doi.org/10.1038/s41598-025-29669-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-11-23 15:56:59","publishedOnDateReadable":"November 23rd, 2025"},"versionCreatedAt":"2025-09-18 09:23:01","video":"","vorDoi":"10.1038/s41598-025-29669-w","vorDoiUrl":"https://doi.org/10.1038/s41598-025-29669-w","workflowStages":[]},"version":"v1","identity":"rs-7415246","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7415246","identity":"rs-7415246","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}