Articles | Volume 10, issue 4
https://doi.org/10.5194/amt-10-1557-2017
© 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-10-1557-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
25 Apr 2017
Research article |
| 25 Apr 2017
Data-driven clustering of rain events: microphysics information derived from macro-scale observations
Mohamed Djallel Dilmi
LATMOS-CNRS/UVSQ/UPSay, 11 boulevard d'Alembert, 78280 Guyancourt,
France
Cécile Mallet
LATMOS-CNRS/UVSQ/UPSay, 11 boulevard d'Alembert, 78280 Guyancourt,
France
Laurent Barthes
CORRESPONDING AUTHOR
LATMOS-CNRS/UVSQ/UPSay, 11 boulevard d'Alembert, 78280 Guyancourt,
France
Aymeric Chazottes
LATMOS-CNRS/UVSQ/UPSay, 11 boulevard d'Alembert, 78280 Guyancourt,
France
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Cited
18 citations as recorded by crossref.
- Probability distribution analysis of extreme rainfall events in a flood-prone region of Mumbai, India A. Parchure & S. Gedam https://doi.org/10.1007/s12517-019-4473-2
- Precipitation Regionalization Using Self-Organizing Maps for Mumbai City, India A. Parchure & S. Gedam https://doi.org/10.4236/jwarp.2018.109055
- Iterative multiscale dynamic time warping (IMs-DTW): a tool for rainfall time series comparison M. Dilmi et al. https://doi.org/10.1007/s41060-019-00193-1
- A Geostationary Satellite Precipitation Estimation Machine Learning Model With Dynamic Sample Balancing for Fengyun-4B H. Sai et al. https://doi.org/10.1109/TGRS.2026.3681960
- Intra-event extreme rainfall characterization in the tropical Andes: a high-resolution weather radar approach G. Urgilés et al. https://doi.org/10.3389/frsen.2026.1793996
- Coupling Poisson rectangular pulse and multiplicative microcanonical random cascade models to generate sub-daily precipitation timeseries I. Pohle et al. https://doi.org/10.1016/j.jhydrol.2018.04.063
- Clustering of Rainfall Types Using Micro Rain Radar and Laser Disdrometer Observations in the Tropical Andes G. Urgilés et al. https://doi.org/10.3390/rs13050991
- Clustering and Characteristic Analysis of Sub-daily Scale (< 12 h) Heavy Rainfall Types in South Korea Based on Observed Rainfall Data H. Yu et al. https://doi.org/10.1007/s13143-025-00412-9
- Multivariable Characterization of Atmospheric Environment with Data Collected in Flight A. Shakirova et al. https://doi.org/10.3390/atmos13101715
- Self-organising maps for rain event classification in Mumbai City, India A. Parchure & S. Gedam https://doi.org/10.1080/09715010.2019.1581099
- A new method of identifying an appropriate distance between independent extreme annual rain events for a 5-min time resolution precipitation data network G. Tardivo et al. https://doi.org/10.1007/s00704-022-04043-2
- Gaussian Mixture Model-Based Cloud- Phase Estimation From GEO- KOMPSAT-2A Observations D. Kim & D. Shin https://doi.org/10.1109/TGRS.2024.3383888
- Toward more robust net primary production projections in the North Atlantic Ocean S. Doléac et al. https://doi.org/10.5194/bg-22-841-2025
- Identification of spatio‐temporal patterns in extreme rainfall events in the Tropical Andes: A clustering analysis approach G. Urgilés et al. https://doi.org/10.1002/met.70005
- Arabic Web page clustering: A review H. Alghamdi & A. Selamat https://doi.org/10.1016/j.jksuci.2017.06.002
- Characterisation of rainfall events in northern Tunisia using self-organising maps S. Derouiche et al. https://doi.org/10.1016/j.ejrh.2022.101159
- Deriving Tropical Cyclone-Associated Flood Hazard Information Using Clustered GPM-IMERG Rainfall Signatures: Case Study in Dominica C. Nabukulu et al. https://doi.org/10.3390/atmos15091042
- Accounting for temporal variability for improved precipitation regionalization based on self-organizing map coupled with information theory R. Guntu et al. https://doi.org/10.1016/j.jhydrol.2020.125236
18 citations as recorded by crossref.
- Probability distribution analysis of extreme rainfall events in a flood-prone region of Mumbai, India A. Parchure & S. Gedam https://doi.org/10.1007/s12517-019-4473-2
- Precipitation Regionalization Using Self-Organizing Maps for Mumbai City, India A. Parchure & S. Gedam https://doi.org/10.4236/jwarp.2018.109055
- Iterative multiscale dynamic time warping (IMs-DTW): a tool for rainfall time series comparison M. Dilmi et al. https://doi.org/10.1007/s41060-019-00193-1
- A Geostationary Satellite Precipitation Estimation Machine Learning Model With Dynamic Sample Balancing for Fengyun-4B H. Sai et al. https://doi.org/10.1109/TGRS.2026.3681960
- Intra-event extreme rainfall characterization in the tropical Andes: a high-resolution weather radar approach G. Urgilés et al. https://doi.org/10.3389/frsen.2026.1793996
- Coupling Poisson rectangular pulse and multiplicative microcanonical random cascade models to generate sub-daily precipitation timeseries I. Pohle et al. https://doi.org/10.1016/j.jhydrol.2018.04.063
- Clustering of Rainfall Types Using Micro Rain Radar and Laser Disdrometer Observations in the Tropical Andes G. Urgilés et al. https://doi.org/10.3390/rs13050991
- Clustering and Characteristic Analysis of Sub-daily Scale (< 12 h) Heavy Rainfall Types in South Korea Based on Observed Rainfall Data H. Yu et al. https://doi.org/10.1007/s13143-025-00412-9
- Multivariable Characterization of Atmospheric Environment with Data Collected in Flight A. Shakirova et al. https://doi.org/10.3390/atmos13101715
- Self-organising maps for rain event classification in Mumbai City, India A. Parchure & S. Gedam https://doi.org/10.1080/09715010.2019.1581099
- A new method of identifying an appropriate distance between independent extreme annual rain events for a 5-min time resolution precipitation data network G. Tardivo et al. https://doi.org/10.1007/s00704-022-04043-2
- Gaussian Mixture Model-Based Cloud- Phase Estimation From GEO- KOMPSAT-2A Observations D. Kim & D. Shin https://doi.org/10.1109/TGRS.2024.3383888
- Toward more robust net primary production projections in the North Atlantic Ocean S. Doléac et al. https://doi.org/10.5194/bg-22-841-2025
- Identification of spatio‐temporal patterns in extreme rainfall events in the Tropical Andes: A clustering analysis approach G. Urgilés et al. https://doi.org/10.1002/met.70005
- Arabic Web page clustering: A review H. Alghamdi & A. Selamat https://doi.org/10.1016/j.jksuci.2017.06.002
- Characterisation of rainfall events in northern Tunisia using self-organising maps S. Derouiche et al. https://doi.org/10.1016/j.ejrh.2022.101159
- Deriving Tropical Cyclone-Associated Flood Hazard Information Using Clustered GPM-IMERG Rainfall Signatures: Case Study in Dominica C. Nabukulu et al. https://doi.org/10.3390/atmos15091042
- Accounting for temporal variability for improved precipitation regionalization based on self-organizing map coupled with information theory R. Guntu et al. https://doi.org/10.1016/j.jhydrol.2020.125236
Saved (final revised paper)
Latest update: 09 Aug 2026
Short summary
The concept of a rain event is used to obtain a parsimonious characterisation of rain events using a minimal subset of variables at macrophysical scale. A classification in five classes is obtained in a unsupervised way from this subset. Relationships between these classes of microphysical parameters of precipitation are highlighted. There are several implications especially for remote sensing in the context of weather radar applications and quantitative precipitation estimation.
The concept of a rain event is used to obtain a parsimonious characterisation of rain events...
