35 citations as recorded by crossref.

1. A study of the 21 March 2012 tornadic quasi linear convective system in Catalonia J. Bech et al. https://doi.org/10.1016/j.atmosres.2014.08.009
2. Spatial Structure of Lightning and Precipitation Associated with Lightning-Caused Wildfires in the Central to Eastern United States B. Vant-Hull & W. Koshak https://doi.org/10.3390/fire6070262
3. Lightning jump as a nowcast predictor: Application to severe weather events in Catalonia C. Farnell et al. https://doi.org/10.1016/j.atmosres.2016.08.021
4. Characterisation of thunderstorms that caused lightning-ignited wildfires A. Soler et al. https://doi.org/10.1071/WF21076
5. Connecting flash flood events with radar-derived convective storm characteristics on the northwestern Mediterranean coast: knowing the present for better future scenarios adaptation A. del Moral et al. https://doi.org/10.1016/j.atmosres.2020.104863
6. Warm Rain Analysis from Remote Sensing Data in the Metropolitan Area of Barcelona for 2015–2022 T. Rigo https://doi.org/10.3390/hydrology10070142
7. An automated nowcasting system of mesoscale convective systems for the Mediterranean basin using Meteosat imagery. Part I: System description S. Kolios & H. Feidas https://doi.org/10.1002/met.1282
8. Probing the precipitation life cycle by iterative rain cell tracking C. Moseley et al. https://doi.org/10.1002/2013JD020868
9. Preliminary Analysis of Early Identification of Three-Body Scatter Spike Signature in Hailstorms in Catalonia T. Rigo & C. Farnell https://doi.org/10.3390/atmos14020269
10. Characterising the dynamic movement of thunderstorms using very low- and low-frequency (VLF/LF) total lightning data over the Pearl River Delta region S. Cheng et al. https://doi.org/10.5194/acp-22-10045-2022
11. Exploring radar and lightning variables associated with the Lightning Jump. Can we predict the size of the hail? C. Farnell et al. https://doi.org/10.1016/j.atmosres.2017.11.019
12. An object-based climatology of precipitation systems in Sydney, Australia H. Ayat et al. https://doi.org/10.1007/s00382-022-06404-z
13. Charge structure analysis of a severe hailstorm with predominantly positive cloud-to-ground lightning N. Pineda et al. https://doi.org/10.1016/j.atmosres.2016.03.010
14. Application of cokriging techniques for the estimation of hail size C. Farnell et al. https://doi.org/10.1007/s00704-016-1937-0
15. Identification of anomalous motion of thunderstorms using daily rainfall fields A. Moral et al. https://doi.org/10.1016/j.atmosres.2016.11.001
16. A New Thunderstorm Identification Algorithm Based on Total Lightning Activity Y. Huang et al. https://doi.org/10.1029/2021EA002079
17. Assimilation of Indian Doppler Weather Radar observations for simulation of mesoscale features of a land-falling cyclone K. Srivastava et al. https://doi.org/10.1007/s11069-011-9835-3
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. An observational analysis of two companion supercell storms over complex terrain T. Rigo et al. https://doi.org/10.1016/j.atmosres.2022.106149
20. Meteorological aspects of heavy precipitation in relation to floods – An overview A. Breugem et al. https://doi.org/10.1016/j.earscirev.2020.103171
21. A Deep Learning Network for Cloud-to-Ground Lightning Nowcasting with Multisource Data K. Zhou et al. https://doi.org/10.1175/JTECH-D-19-0146.1
22. A Mediterranean nocturnal heavy rainfall and tornadic event. Part II: Total lightning analysis N. Pineda et al. https://doi.org/10.1016/j.atmosres.2010.10.027
23. The Lightning Jump Algorithm for Nowcasting Convective Rainfall in Catalonia C. Farnell & T. Rigo https://doi.org/10.3390/atmos11040397
24. Remote sensing analysis of a Mediterranean thundersnow and low-altitude heavy snowfall event J. Bech et al. https://doi.org/10.1016/j.atmosres.2012.06.021
25. An improved analysis of mesoscale convective systems in the western Mediterranean using weather radar T. Rigo et al. https://doi.org/10.1016/j.atmosres.2019.05.001
26. 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
27. Toward a Deep-Learning-Network-Based Convective Weather Initiation Algorithm From the Joint Observations of Fengyun-4A Geostationary Satellite and Radar for 0–1h Nowcasting F. Sun et al. https://doi.org/10.1109/JSTARS.2023.3262557
28. A radar-based centroid tracking algorithm for severe weather surveillance: identifying split/merge processes in convective systems A. del Moral et al. https://doi.org/10.1016/j.atmosres.2018.05.030
29. Characteristics of thunderstorm cores from observations in Yakutia V. Kozlov et al. https://doi.org/10.1007/s11182-013-0048-y
30. Statistical Characteristics of Thunderstorm Activity in the Middle Reaches of the Yangtze River Basin Based on a Five‐Year Cloud‐To‐Ground Lighting Data Set Q. Wei et al. https://doi.org/10.1029/2023GL106498
31. Forecasting hailfall using parameters for convective cells identified by radar T. Rigo & M. Carmen Llasat https://doi.org/10.1016/j.atmosres.2015.10.021
32. Evaluation of the Radar Echo Tops in Catalonia: Relationship with Severe Weather T. Rigo & C. Farnell Barqué https://doi.org/10.3390/rs14246265
33. Total lightning signatures of thunderstorms and lightning jumps in hailfall nowcasting in the Beijing area Y. Tian et al. https://doi.org/10.1016/j.atmosres.2019.104646
34. A Mediterranean nocturnal heavy rainfall and tornadic event. Part I: Overview, damage survey and radar analysis J. Bech et al. https://doi.org/10.1016/j.atmosres.2010.12.024
35. Reanalysis of Giant Hail Event in Catalonia (NE of the Iberian Peninsula) C. Farnell et al. https://doi.org/10.1016/j.atmosres.2023.107051