36 citations as recorded by crossref.

1. Lightning activity, rainfall and flash flooding – occasional or interrelated events? A case study in the island of Crete A. Koutroulis et al. https://doi.org/10.5194/nhess-12-881-2012
2. Lightning and convective rain over Indian peninsula and Indo-China peninsula D. Siingh et al. https://doi.org/10.1016/j.asr.2014.11.014
3. Relationship Between Convective Storm Properties and Lightning Over the Western Ghats B. Utsav et al. https://doi.org/10.1029/2022EA002232
4. Lightning Sensors for Observing, Tracking and Nowcasting Severe Weather C. Price https://doi.org/10.3390/s8010157
5. Thunderstorm Efficiency Regimes in South America as Observed by STARNET and TRMM C. Morales Rodriguez https://doi.org/10.1029/2019JD030950
6. Diurnal and spatial variabilities of monsoonal CG lightning and precipitation and their association with the synoptic weather conditions over South Korea Y. Hyun et al. https://doi.org/10.1007/s00704-009-0235-5
7. Evaluation of Lightning Forecasting Based on One Lightning Parameterization Scheme and Two Diagnostic Methods Y. Wang et al. https://doi.org/10.3390/atmos9030099
8. Analysis of Lightning and Precipitation Activities in Three Severe Convective Events Based on Doppler Radar and Microwave Radiometer over the Central China Region J. Sun et al. https://doi.org/10.3390/atmos10060298
9. Clouds’ Microphysical Properties and Their Relationship with Lightning Activity in Northeast Brazil L. de Abreu et al. https://doi.org/10.3390/rs13214491
10. Thunderstorm climatology in the Mediterranean using cloud-to-ground lightning observations E. Galanaki et al. https://doi.org/10.1016/j.atmosres.2018.03.004
11. Performance of ECMWF forecasts for convective events using radar-based and multi-source observations J. Cruz et al. https://doi.org/10.1016/j.atmosres.2026.109051
12. Analysis of lightning flash rate with the occurrence of flash floods and hailstorms in Peninsular Malaysia N. Bahari et al. https://doi.org/10.1016/j.jastp.2023.106121
13. Improving forecasting of strong convection by assimilating cloud-to-ground lightning data using the physical initialization method Y. Wang et al. https://doi.org/10.1016/j.atmosres.2014.06.017
14. Seasonal variations on the conditions required for the lightning production A. Salvador et al. https://doi.org/10.1016/j.atmosres.2020.104981
15. Improving GSMaP Precipitation Estimates Using a Modified Kalman Filter With Lightning Flash Rate A. Veloria et al. https://doi.org/10.1109/TGRS.2026.3659805
16. Lightning and convective rain study in different parts of India D. Siingh et al. https://doi.org/10.1016/j.atmosres.2013.09.018
17. Recent advances in research of lightning meteorology X. Qie et al. https://doi.org/10.1007/s13351-014-3295-0
18. Evolution of Radar and Lightning Variables in Convective Events in Barcelona and Surroundings for the Period 2006–2020 T. Rigo & S. Castillo https://doi.org/10.21926/aeer.2102004
19. A model for global biomass burning in preindustrial time: LPJ-LMfire (v1.0) M. Pfeiffer et al. https://doi.org/10.5194/gmd-6-643-2013
20. Cloud‐to‐ground lightning and surface rainfall in warm‐season Florida thunderstorms B. Gungle & E. Krider https://doi.org/10.1029/2005JD006802
21. Cloud-to-ground lightning and Mesoscale Convective Systems E. Mattos & L. Machado https://doi.org/10.1016/j.atmosres.2010.11.007
22. Application of total-lightning data assimilation in a mesoscale convective system based on the WRF model X. Qie et al. https://doi.org/10.1016/j.atmosres.2014.04.012
23. Predicting the potential for lightning activity in Mediterranean storms based on the Weather Research and Forecasting (WRF) model dynamic and microphysical fields Y. Yair et al. https://doi.org/10.1029/2008JD010868
24. A thunderstorm cell-lightning activity analysis: The new concept of air mass catchment T. Mona et al. https://doi.org/10.1016/j.atmosres.2015.10.017
25. A Convolutional Neural Network for Lightning Strikes Detection Over the Italian Territory Using SEVIRI@MSG Data P. Duminuco et al. https://doi.org/10.1109/TGRS.2025.3641256
26. Simulating lightning into the RAMS model: implementation and preliminary results S. Federico et al. https://doi.org/10.5194/nhess-14-2933-2014
27. Electric systems failures produced by CG lightning in Eastern Amazonia A. Santos et al. https://doi.org/10.1590/0102-778620130028
28. Can the Correlation between Radar and Cloud-to-Ground Daily Fields Help to Identify the Different Rainfall Regimes? The Case of Catalonia S. Castillo et al. https://doi.org/10.3390/atmos13050808
29. On the Relation Between Cloud-to-Ground Lightning and Rainfall During 2006 and 2007 Summer Cases S. Oh et al. https://doi.org/10.5467/JKESS.2010.31.7.749
30. WRF-LTNGDA: A lightning data assimilation technique implemented in the WRF model for improving precipitation forecasts T. Giannaros et al. https://doi.org/10.1016/j.envsoft.2015.11.017
31. The correlation between lightning and DSD parameters J. Saylor et al. https://doi.org/10.1109/TGRS.2005.851638
32. Nowcasting thunderstorms in the Mediterranean region using lightning data M. Kohn et al. https://doi.org/10.1016/j.atmosres.2010.08.010
33. A Case Study of Assimilating Lightning-Proxy Relative Humidity with WRF-3DVAR Y. Wang et al. https://doi.org/10.3390/atmos8030055
34. Using a cloud electrification model to study relationships between lightning activity and cloud microphysical structure M. Formenton et al. https://doi.org/10.5194/nhess-13-1085-2013
35. Lightning and precipitation relationship in summer thunderstorms: Case studies in the North Western Mediterranean region N. Pineda et al. https://doi.org/10.1016/j.atmosres.2006.12.004
36. On the association between lightning and precipitation microphysics C. Chatterjee & S. Das https://doi.org/10.1016/j.jastp.2020.105350