71 citations as recorded by crossref.

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2. Impact of Lightning‐Induced Nitrogen Oxides Over and Around the Tibetan Plateau on the Tibetan Plateau Ozone Valley Z. Liu et al. 10.1029/2023JD039575
3. Lightning NOx, a key chemistry–climate interaction: impacts of future climate change and consequences for tropospheric oxidising capacity A. Banerjee et al. 10.5194/acp-14-9871-2014
4. WRF-GC (v2.0): online two-way coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.7.2) for modeling regional atmospheric chemistry–meteorology interactions X. Feng et al. 10.5194/gmd-14-3741-2021
5. Lightning forecasting in Bangladesh based on the lightning potential index and the electric potential K. Rabbani et al. 10.1016/j.atmosres.2021.105973
6. Probabilistic Forecasting of Lightning Strikes over the Continental USA and Alaska: Model Development and Verification N. Nikolov et al. 10.3390/fire7040111
7. European NOx emissions in WRF-Chem derived from OMI: impacts on summertime surface ozone A. Visser et al. 10.5194/acp-19-11821-2019
8. Understanding the impact of ice nucleation on lightning and rainfall: A case study A. Hazra et al. 10.1016/j.atmosres.2022.106350
9. Evaluating the performance and detection efficiency of Weather Research Forecasting model with lightning parameterization schemes for identifying lightning hotspots over Northeast region in India U. Mondal et al. 10.1007/s00382-024-07457-y
10. Wet Scavenging in WRF‐Chem Simulations of Parameterized Convection for a Severe Storm During the DC3 Field Campaign Y. Li et al. 10.1029/2019JD030484
11. Predicting lightning activity in Greece with the Weather Research and Forecasting (WRF) model T. Giannaros et al. 10.1016/j.atmosres.2014.12.009
12. Satellite soil moisture data assimilation impacts on modeling weather variables and ozone in the southeastern US – Part 1: An overview M. Huang et al. 10.5194/acp-21-11013-2021
13. The use of lightning data and Meteosat infrared imagery for the nowcasting of lightning activity A. Karagiannidis et al. 10.1016/j.atmosres.2015.08.011
14. Performance evaluation of an operational lightning forecasting system in Europe T. Giannaros et al. 10.1007/s11069-016-2555-y
15. Improving Lake-Breeze Simulation with WRF Nested LES and Lake Model over a Large Shallow Lake X. Zhang et al. 10.1175/JAMC-D-18-0282.1
16. Implications of Sea Breezes on Air Quality Monitoring in a Coastal Urban Environment: Evidence From High Resolution Modeling of NO2 and O3 B. Wang et al. 10.1029/2022JD037860
17. Using cloud ice flux to parametrise large-scale lightning D. Finney et al. 10.5194/acp-14-12665-2014
18. Development of a self‐consistent lightning NOx simulation in large‐scale 3‐D models C. Luo et al. 10.1002/2016JD026225
19. Lightning Over Central Canada: Skill Assessment for Various Land‐Atmosphere Model Configurations and Lightning Indices Over a Boreal Study Area J. Mortelmans et al. 10.1029/2022JD037236
20. Seasonality in power law scaling of convective and stratiform rainfall with lightning intensity over Indian Monsoon regions B. Choudhury et al. 10.1016/j.atmosres.2020.105265
21. Reactive nitrogen in and around the northeastern and mid-Atlantic US: sources, sinks, and connections with ozone M. Huang et al. 10.5194/acp-25-1449-2025
22. 基于气象大模型的门控时空融合网络闪电预报方法 怡. 李 et al. 10.1360/SSTe-2025-0001
23. The Impact of High-Resolution SRTM Topography and Corine Land Cover on Lightning Calculations in WRF A. de Meij et al. 10.3390/atmos13071050
24. The impact of lightning on tropospheric ozone chemistry using a new global lightning parametrisation D. Finney et al. 10.5194/acp-16-7507-2016
25. Evaluation of Lightning Forecasting Based on One Lightning Parameterization Scheme and Two Diagnostic Methods Y. Wang et al. 10.3390/atmos9030099
26. Seasonal and Regional Distribution of Lightning Fraction Over Indian Subcontinent R. Ghosh et al. 10.1029/2022EA002728
27. Prediction of lightning activity using WRF-ELEC model: Impact of initial and boundary conditions M. Gharaylou et al. 10.1016/j.jastp.2020.105438
28. Comparison of Lightning Forecasts from the High-Resolution Rapid Refresh Model to Geostationary Lightning Mapper Observations B. Blaylock & J. Horel 10.1175/WAF-D-19-0141.1
29. Constraining the budget of NOx and volatile organic compounds at a remote tropical island using multi-platform observations and WRF-Chem model simulations C. Poraicu et al. 10.5194/acp-25-6903-2025
30. Significant contribution of lightning NO to summertime surface O3 on the Tibetan Plateau M. Li et al. 10.1016/j.scitotenv.2022.154639
31. Simulation of premonsoon thunderclouds over two climatic regimes: evaluation and dichotomous detection R. Biswasharma et al. 10.1016/j.atmosres.2025.108027
32. Attention-Based Dual-Source Spatiotemporal Neural Network for Lightning Forecast T. Lin et al. 10.1109/ACCESS.2019.2950328
33. Sensitivity analysis of weather research and forecasting (WRF) model output variables to the thunderstorm lifecycle and its application H. Huang et al. 10.1007/s11069-022-05455-z
34. Distinct aerosol effects on cloud-to-ground lightning in the plateau and basin regions of Sichuan, Southwest China P. Zhao et al. 10.5194/acp-20-13379-2020
35. Evaluation and Usefulness of Lightning Forecasts Made with Lightning Parameterization Schemes Coupled with the WRF Model G. Vani K. et al. 10.1175/WAF-D-21-0080.1
36. Modeling lightning density using cloud top parameters A. Karagiannidis et al. 10.1016/j.atmosres.2019.02.013
37. Lightning NO2 simulation over the contiguous US and its effects on satellite NO2 retrievals Q. Zhu et al. 10.5194/acp-19-13067-2019
38. Estimates of lightning NOx production based on high-resolution OMI NO2 retrievals over the continental US X. Zhang et al. 10.5194/amt-13-1709-2020
39. Prediction of lightning activity over Bangladesh using diagnostic and explicit lightning parameterizations of WRF model M. Paramanik et al. 10.1007/s11069-023-06355-6
40. Global association of aerosol with flash density of intense lightning O. Altaratz et al. 10.1088/1748-9326/aa922b
41. Examining relationships between cloud‐resolving model parameters and total flash rates to generate lightning density maps C. Bovalo et al. 10.1002/qj.3494
42. Evaluation of Lightning Prediction by an Electrification and Discharge Model in Long-Term Forecasting Experiments L. Xu et al. 10.1155/2022/4583030
43. Evaluating different lightning parameterization schemes to simulate lightning flash counts over Maharashtra, India G. Mohan et al. 10.1016/j.atmosres.2021.105532
44. WRF-ELEC lightning validation with IITM-LLN: Performance across the Indian subcontinent B. Choudhury et al. 10.1007/s12040-025-02534-0
45. Seasonal prediction of lightning activity in North Western Venezuela: Large-scale versus local drivers Á. Muñoz et al. 10.1016/j.atmosres.2015.12.018
46. LightNet+: A dual-source lightning forecasting network with bi-direction spatiotemporal transformation X. Zhou et al. 10.1007/s10489-021-03089-5
47. Performance Evaluation of an Explicit Lightning Forecasting System S. Dafis et al. 10.1029/2017JD027930
48. Modeling cloud-to-ground lightning probability in Alaskan tundra through the integration of Weather Research and Forecast (WRF) model and machine learning method J. He & T. Loboda 10.1088/1748-9326/abbc3b
49. Assimilation of Meteosat Third Generation (MTG) Lightning Imager (LI) pseudo-observations in AROME-France – proof of concept F. Erdmann et al. 10.5194/nhess-23-2821-2023
50. A satellite lightning observation operator for storm-scale numerical weather prediction P. Combarnous et al. 10.5194/nhess-22-2943-2022
51. Simulating lightning into the RAMS model: implementation and preliminary results S. Federico et al. 10.5194/nhess-14-2933-2014
52. CORDEX-WRF v1.3: development of a module for the Weather Research and Forecasting (WRF) model to support the CORDEX community L. Fita et al. 10.5194/gmd-12-1029-2019
53. Changes in Cu Characteristics and Precipitation during Cu Merging A. Sin’kevich et al. 10.3103/S1068373918080022
54. Reviews and perspectives of high impact atmospheric processes in the Mediterranean S. Michaelides et al. 10.1016/j.atmosres.2017.11.022
55. Improvements to the WRF-Chem 3.5.1 model for quasi-hemispheric simulations of aerosols and ozone in the Arctic L. Marelle et al. 10.5194/gmd-10-3661-2017
56. Box Model Intercomparison of Cloud Chemistry M. Barth et al. 10.1029/2021JD035486
57. A gated spatiotemporal fusion network for lightning forecasting based on weather foundation models Y. Li et al. 10.1007/s11430-025-1638-8
58. Quantification of the effect of modeled lightning NO2 on UV–visible air mass factors J. Laughner & R. Cohen 10.5194/amt-10-4403-2017
59. Association of lightning occurrence with precipitation cloud column structure at a fixed position Y. Cui et al. 10.1016/j.atmosres.2021.105989
60. Response of lightning NOx emissions and ozone production to climate change: Insights from the Atmospheric Chemistry and Climate Model Intercomparison Project D. Finney et al. 10.1002/2016GL068825
61. Assessment of Updated Fuel‐Based Emissions Inventories Over the Contiguous United States Using TROPOMI NO2 Retrievals M. Li et al. 10.1029/2021JD035484
62. The impacts of shipping emissions on lightning: roles of aerosol-radiation-interactions and aerosol-cloud-interactions R. Sun et al. 10.1088/1748-9326/ad2aba
63. The POLARCAT Model Intercomparison Project (POLMIP): overview and evaluation with observations L. Emmons et al. 10.5194/acp-15-6721-2015
64. Improving the lightning forecast with the WRF model and lightning data assimilation: Results of a two-seasons numerical experiment over Italy S. Federico et al. 10.1016/j.atmosres.2024.107382
65. Interpretable artificial intelligence models for predicting lightning prone to inducing forest fires S. Song et al. 10.1016/j.jastp.2024.106408
66. Anak Krakatau triggers volcanic freezer in the upper troposphere A. Prata et al. 10.1038/s41598-020-60465-w
67. Impact of Lightning NOx Emissions on Atmospheric Composition and Meteorology in Africa and Europe L. Menut et al. 10.3390/atmos11101128
68. Unveiling India’s lightning patterns through satellite-based climatology and numerical modelling of severe weather events: A review U. Mondal et al. 10.1007/s12040-024-02491-0
69. A physics-based ensemble machine-learning approach to identifying a relationship between lightning indices and binary lightning hazard A. Thomas & S. Noble 10.3389/feart.2024.1376605
70. A Year-Long Total Lightning Forecast over Italy with a Dynamic Lightning Scheme and WRF S. Federico et al. 10.3390/rs14143244
71. Thunderstorms and upper troposphere chemistry during the early stages of the 2006 North American Monsoon M. Barth et al. 10.5194/acp-12-11003-2012