Articles | Volume 10, issue 1
https://doi.org/10.5194/amt-10-221-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-10-221-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Observing relationships between lightning and cloud profiles by means of a satellite-borne cloud radar
Martina Buiat
University of Ferrara, Dept. of Physics and Earth Sciences, Ferrara,
Italy
University of Bologna, Dept. of Physics and Astronomy, Bologna, Italy
Stefano Dietrich
Institute of Atmospheric Sciences and Climate (ISAC), National
Research Council of Italy (CNR), Rome, Italy
Viewed
Total article views: 3,154 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 28 Apr 2016)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,920 | 861 | 373 | 3,154 | 128 | 120 |
- HTML: 1,920
- PDF: 861
- XML: 373
- Total: 3,154
- BibTeX: 128
- EndNote: 120
Total article views: 2,691 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 18 Jan 2017)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,656 | 671 | 364 | 2,691 | 124 | 111 |
- HTML: 1,656
- PDF: 671
- XML: 364
- Total: 2,691
- BibTeX: 124
- EndNote: 111
Total article views: 463 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 28 Apr 2016)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
264 | 190 | 9 | 463 | 4 | 9 |
- HTML: 264
- PDF: 190
- XML: 9
- Total: 463
- BibTeX: 4
- EndNote: 9
Cited
11 citations as recorded by crossref.
- Analysis of the lightning production of convective cells J. Figueras i Ventura et al. 10.5194/amt-12-5573-2019
- Probabilistic Forecasting of Lightning Strikes over the Continental USA and Alaska: Model Development and Verification N. Nikolov et al. 10.3390/fire7040111
- Possible roles of fall speed parameters of different graupel densities on microphysics and electrification in an idealized thunderstorm X. Ouyang et al. 10.1002/qj.3569
- Impact of electrified and non-electrified clouds on the inter-seasonal characteristics of surface-based precipitation K. Chakravarty et al. 10.1007/s12040-020-01432-x
- Lightning Detection Using GEO-KOMPSAT-2A/Advanced Meteorological Imager and Ground-Based Lightning Observation Sensor LINET Data S. Lee & M. Suh 10.3390/rs16224243
- 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
- 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
- A CloudSat and CALIPSO‐Based Evaluation of the Effects of Thermodynamic Instability and Aerosol Loading on Amazon Basin Deep Convection and Lightning D. Allen et al. 10.1029/2023JD039818
- On the association between lightning and precipitation microphysics C. Chatterjee & S. Das 10.1016/j.jastp.2020.105350
- A 13-year long strokes statistical analysis over the Central Mediterranean area M. Petracca et al. 10.1016/j.atmosres.2024.107368
- Characteristic differences between two contrasting tropical squalls C. Chatterjee & S. Das 10.1007/s12040-023-02064-7
11 citations as recorded by crossref.
- Analysis of the lightning production of convective cells J. Figueras i Ventura et al. 10.5194/amt-12-5573-2019
- Probabilistic Forecasting of Lightning Strikes over the Continental USA and Alaska: Model Development and Verification N. Nikolov et al. 10.3390/fire7040111
- Possible roles of fall speed parameters of different graupel densities on microphysics and electrification in an idealized thunderstorm X. Ouyang et al. 10.1002/qj.3569
- Impact of electrified and non-electrified clouds on the inter-seasonal characteristics of surface-based precipitation K. Chakravarty et al. 10.1007/s12040-020-01432-x
- Lightning Detection Using GEO-KOMPSAT-2A/Advanced Meteorological Imager and Ground-Based Lightning Observation Sensor LINET Data S. Lee & M. Suh 10.3390/rs16224243
- 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
- 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
- A CloudSat and CALIPSO‐Based Evaluation of the Effects of Thermodynamic Instability and Aerosol Loading on Amazon Basin Deep Convection and Lightning D. Allen et al. 10.1029/2023JD039818
- On the association between lightning and precipitation microphysics C. Chatterjee & S. Das 10.1016/j.jastp.2020.105350
- A 13-year long strokes statistical analysis over the Central Mediterranean area M. Petracca et al. 10.1016/j.atmosres.2024.107368
- Characteristic differences between two contrasting tropical squalls C. Chatterjee & S. Das 10.1007/s12040-023-02064-7
Latest update: 14 Dec 2024
Short summary
The cloud radar on board the NASA CloudSat mission provides information on the vertical structure of the cloud that, in the present study, is matched to ground-based measurements of lightning occurrences. The aim of this research was to study the relationship between the ice content of the cloud and its capability to produce lightning. Results show the importance of high ice content, especially close to the cloud top, for producing lightning.
The cloud radar on board the NASA CloudSat mission provides information on the vertical...