Articles | Volume 14, issue 4
https://doi.org/10.5194/nhess-14-1017-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-14-1017-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
29 Apr 2014
Research article |
| 29 Apr 2014
Daytime identification of summer hailstorm cells from MSG data
A. Merino
Group for Atmospheric Physics, IMA, University of León, Leon, Spain
L. López
Group for Atmospheric Physics, IMA, University of León, Leon, Spain
J. L. Sánchez
Group for Atmospheric Physics, IMA, University of León, Leon, Spain
E. García-Ortega
Group for Atmospheric Physics, IMA, University of León, Leon, Spain
E. Cattani
National Research Council of Italy, Institute of Atmospheric Sciences and Climate, CNR-ISAC, Bologna, Italy
V. Levizzani
National Research Council of Italy, Institute of Atmospheric Sciences and Climate, CNR-ISAC, Bologna, Italy
Viewed
Total article views: 4,556 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 11 Oct 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,942 | 2,323 | 291 | 4,556 | 192 | 207 |
- HTML: 1,942
- PDF: 2,323
- XML: 291
- Total: 4,556
- BibTeX: 192
- EndNote: 207
Total article views: 3,783 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 29 Apr 2014)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,684 | 1,827 | 272 | 3,783 | 179 | 196 |
- HTML: 1,684
- PDF: 1,827
- XML: 272
- Total: 3,783
- BibTeX: 179
- EndNote: 196
Total article views: 773 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 11 Oct 2013)
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 258 | 496 | 19 | 773 | 13 | 11 |
- HTML: 258
- PDF: 496
- XML: 19
- Total: 773
- BibTeX: 13
- EndNote: 11
Cited
30 citations as recorded by crossref.
- On the Detection of Hail Using Satellite Passive Microwave Radiometers and Precipitation Radar X. Ni et al. https://doi.org/10.1175/JAMC-D-17-0065.1
- Hailstorm Detection by Satellite Microwave Radiometers S. Laviola et al. https://doi.org/10.3390/rs12040621
- Hail observations and hailstorm characteristics in Europe: A review H. Punge & M. Kunz https://doi.org/10.1016/j.atmosres.2016.02.012
- A New Method for Hail Detection from the GPM Constellation: A Prospect for a Global Hailstorm Climatology S. Laviola et al. https://doi.org/10.3390/rs12213553
- Hail detection from Meteosat satellite imagery using a deep learning neural network and a new remote sensing index S. Kolios https://doi.org/10.1016/j.asr.2023.06.016
- Triggering and evolution of a deep convective system in the Mediterranean Sea: modelling and observations at a very fine scale E. Fiori et al. https://doi.org/10.1002/qj.2977
- Spatiotemporal variability of precipitation characteristics in hailstorm based on the observations of spaceborne precipitation radar Y. Zhang & X. Ni https://doi.org/10.1016/j.atmosres.2025.108346
- Detecting Hailstorms in China from FY-4A Satellite with an Ensemble Machine Learning Model Q. Wu et al. https://doi.org/10.3390/rs16183354
- Prediction of convective events using multi-frequency radiometric observations at Kolkata R. Chakraborty et al. https://doi.org/10.1016/j.atmosres.2015.09.024
- Estimation of Maximum Hail Diameters from FY-4A Satellite Data with a Machine Learning Method Q. Wu et al. https://doi.org/10.3390/rs14010073
- Evaluation of Satellite-Derived Signatures for Three Verified Hailstorms in Central Argentina A. Bernal Ayala et al. https://doi.org/10.3390/meteorology1020013
- Cultural Heritage Resilience in the Face of Extreme Weather: Lessons from the UNESCO Site of Alberobello A. Mascitelli et al. https://doi.org/10.3390/su152115556
- Hail Climatology in the Mediterranean Basin Using the GPM Constellation (1999–2021) S. Laviola et al. https://doi.org/10.3390/rs14174320
- Spatial distribution of thermodynamic conditions of severe storms in southwestern Europe E. Gascón et al. https://doi.org/10.1016/j.atmosres.2015.05.012
- 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
- A Probabilistic Multispectral Pattern Recognition Method for Detection of Overshooting Cloud Tops Using Passive Satellite Imager Observations K. Bedka & K. Khlopenkov https://doi.org/10.1175/JAMC-D-15-0249.1
- Hailfalls in southwest Europe: EOF analysis for identifying synoptic pattern and their trends A. Merino et al. https://doi.org/10.1016/j.atmosres.2018.08.006
- Characteristics of Summer Hailstorms Observed by Radar and Himawari-8 in Beijing, China Y. Jing et al. https://doi.org/10.3390/rs14225843
- A Poisson regression approach to model monthly hail occurrence in Northern Switzerland using large-scale environmental variables E. Madonna et al. https://doi.org/10.1016/j.atmosres.2017.11.024
- Prediction of Rain Occurrence and Accumulation Using Multifrequency Radiometric Observations A. Maitra & R. Chakraborty https://doi.org/10.1109/TGRS.2017.2783848
- Deep feature extraction and its application for hailstorm detection in a large collection of radar images I. Gurung et al. https://doi.org/10.1007/s11760-018-1380-z
- Large hail detection using radar-based VIL calibrated with isotherms from the ERA5 reanalysis W. Pilorz et al. https://doi.org/10.1016/j.atmosres.2022.106185
- Multi-Sensor Data Analysis of an Intense Weather Event: The July 2021 Lake Como Case Study A. Mascitelli et al. https://doi.org/10.3390/w14233916
- Spatial and temporal variability of hail falls and estimation of maximum diameter from meteorological variables J. Marcos et al. https://doi.org/10.1016/j.atmosres.2020.105142
- Nowcasting Extreme Weather with Machine Learning Techniques Applied to Different Input Datasets R. Biondi et al. https://doi.org/10.2139/ssrn.4144317
- Satellite remote sensing of hailstorms in France P. Melcón et al. https://doi.org/10.1016/j.atmosres.2016.08.001
- Probabilistic 0–1-h Convective Initiation Nowcasts that Combine Geostationary Satellite Observations and Numerical Weather Prediction Model Data J. Mecikalski et al. https://doi.org/10.1175/JAMC-D-14-0129.1
- Understanding Hail in the Earth System J. Allen et al. https://doi.org/10.1029/2019RG000665
- Climatology of destructive hailstorms in Brazil J. Martins et al. https://doi.org/10.1016/j.atmosres.2016.10.012
- WRF hourly evaluation for extreme precipitation events A. Merino et al. https://doi.org/10.1016/j.atmosres.2022.106215
30 citations as recorded by crossref.
- On the Detection of Hail Using Satellite Passive Microwave Radiometers and Precipitation Radar X. Ni et al. https://doi.org/10.1175/JAMC-D-17-0065.1
- Hailstorm Detection by Satellite Microwave Radiometers S. Laviola et al. https://doi.org/10.3390/rs12040621
- Hail observations and hailstorm characteristics in Europe: A review H. Punge & M. Kunz https://doi.org/10.1016/j.atmosres.2016.02.012
- A New Method for Hail Detection from the GPM Constellation: A Prospect for a Global Hailstorm Climatology S. Laviola et al. https://doi.org/10.3390/rs12213553
- Hail detection from Meteosat satellite imagery using a deep learning neural network and a new remote sensing index S. Kolios https://doi.org/10.1016/j.asr.2023.06.016
- Triggering and evolution of a deep convective system in the Mediterranean Sea: modelling and observations at a very fine scale E. Fiori et al. https://doi.org/10.1002/qj.2977
- Spatiotemporal variability of precipitation characteristics in hailstorm based on the observations of spaceborne precipitation radar Y. Zhang & X. Ni https://doi.org/10.1016/j.atmosres.2025.108346
- Detecting Hailstorms in China from FY-4A Satellite with an Ensemble Machine Learning Model Q. Wu et al. https://doi.org/10.3390/rs16183354
- Prediction of convective events using multi-frequency radiometric observations at Kolkata R. Chakraborty et al. https://doi.org/10.1016/j.atmosres.2015.09.024
- Estimation of Maximum Hail Diameters from FY-4A Satellite Data with a Machine Learning Method Q. Wu et al. https://doi.org/10.3390/rs14010073
- Evaluation of Satellite-Derived Signatures for Three Verified Hailstorms in Central Argentina A. Bernal Ayala et al. https://doi.org/10.3390/meteorology1020013
- Cultural Heritage Resilience in the Face of Extreme Weather: Lessons from the UNESCO Site of Alberobello A. Mascitelli et al. https://doi.org/10.3390/su152115556
- Hail Climatology in the Mediterranean Basin Using the GPM Constellation (1999–2021) S. Laviola et al. https://doi.org/10.3390/rs14174320
- Spatial distribution of thermodynamic conditions of severe storms in southwestern Europe E. Gascón et al. https://doi.org/10.1016/j.atmosres.2015.05.012
- 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
- A Probabilistic Multispectral Pattern Recognition Method for Detection of Overshooting Cloud Tops Using Passive Satellite Imager Observations K. Bedka & K. Khlopenkov https://doi.org/10.1175/JAMC-D-15-0249.1
- Hailfalls in southwest Europe: EOF analysis for identifying synoptic pattern and their trends A. Merino et al. https://doi.org/10.1016/j.atmosres.2018.08.006
- Characteristics of Summer Hailstorms Observed by Radar and Himawari-8 in Beijing, China Y. Jing et al. https://doi.org/10.3390/rs14225843
- A Poisson regression approach to model monthly hail occurrence in Northern Switzerland using large-scale environmental variables E. Madonna et al. https://doi.org/10.1016/j.atmosres.2017.11.024
- Prediction of Rain Occurrence and Accumulation Using Multifrequency Radiometric Observations A. Maitra & R. Chakraborty https://doi.org/10.1109/TGRS.2017.2783848
- Deep feature extraction and its application for hailstorm detection in a large collection of radar images I. Gurung et al. https://doi.org/10.1007/s11760-018-1380-z
- Large hail detection using radar-based VIL calibrated with isotherms from the ERA5 reanalysis W. Pilorz et al. https://doi.org/10.1016/j.atmosres.2022.106185
- Multi-Sensor Data Analysis of an Intense Weather Event: The July 2021 Lake Como Case Study A. Mascitelli et al. https://doi.org/10.3390/w14233916
- Spatial and temporal variability of hail falls and estimation of maximum diameter from meteorological variables J. Marcos et al. https://doi.org/10.1016/j.atmosres.2020.105142
- Nowcasting Extreme Weather with Machine Learning Techniques Applied to Different Input Datasets R. Biondi et al. https://doi.org/10.2139/ssrn.4144317
- Satellite remote sensing of hailstorms in France P. Melcón et al. https://doi.org/10.1016/j.atmosres.2016.08.001
- Probabilistic 0–1-h Convective Initiation Nowcasts that Combine Geostationary Satellite Observations and Numerical Weather Prediction Model Data J. Mecikalski et al. https://doi.org/10.1175/JAMC-D-14-0129.1
- Understanding Hail in the Earth System J. Allen et al. https://doi.org/10.1029/2019RG000665
- Climatology of destructive hailstorms in Brazil J. Martins et al. https://doi.org/10.1016/j.atmosres.2016.10.012
- WRF hourly evaluation for extreme precipitation events A. Merino et al. https://doi.org/10.1016/j.atmosres.2022.106215
Saved (final revised paper)
Latest update: 23 Aug 2026
Altmetrics
Final-revised paper
Preprint