Articles | Volume 8, issue 1
https://doi.org/10.5194/amt-8-149-2015
© Author(s) 2015. 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-8-149-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
09 Jan 2015
Research article |
| 09 Jan 2015
Hydrometeor classification from polarimetric radar measurements: a clustering approach
J. Grazioli
Environmental Remote Sensing Laboratory (LTE), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Laboratory of Geographic Information Systems (LASIG), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Environmental Remote Sensing Laboratory (LTE), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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- Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach N. Besic et al. 10.5194/amt-9-4425-2016
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- A Support Vector Machine Hydrometeor Classification Algorithm for Dual-Polarization Radar N. Roberto et al. 10.3390/atmos8080134
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- Overview: Fusion of radar polarimetry and numerical atmospheric modelling towards an improved understanding of cloud and precipitation processes S. Trömel et al. 10.5194/acp-21-17291-2021
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- Precipitation and Fatal Motor Vehicle Crashes: Continental Analysis with High-Resolution Radar Data S. Stevens et al. 10.1175/BAMS-D-18-0001.1
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- Hydrometeor classification of quasi-vertical profiles of polarimetric radar measurements using a top-down iterative hierarchical clustering method M. Lukach et al. 10.5194/amt-14-1075-2021
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Saved (final revised paper)
Latest update: 18 Apr 2024
Short summary
A new approach for hydrometeor classification from polarimetric radar measurements is proposed. It takes adavantage of clustering techniques to objectively determine the number of hydrometeor classes that can be reliably identified. The proposed method is tested using observations from an X-band polarimetric radar in different regions and evaluated by comparison with existing algorithms and with measurements from a ground-based 2D video disdrometer (providing 2-D views of falling hydrometeors).
A new approach for hydrometeor classification from polarimetric radar measurements is proposed....
