Articles | Volume 9, issue 9
https://doi.org/10.5194/amt-9-4425-2016
https://doi.org/10.5194/amt-9-4425-2016
Research article
 | 
08 Sep 2016
Research article |  | 08 Sep 2016

Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach

Nikola Besic, Jordi Figueras i Ventura, Jacopo Grazioli, Marco Gabella, Urs Germann, and Alexis Berne

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Cited articles

Al-Sakka, H., Boumahmoud, A.-A., Fradon, B., Frasier, S. J., and Tabary, P.: A New Fuzzy Logic Hydrometeor Classification Scheme Applied to the French X-, C-, and S-Band Polarimetric Radars, J. Atmos. Ocean. Technol., 52, 2328–2344, 2013.
Baldauf, M., Seifert, A., Forstner, J., Majewski, D., Raschendorfer, M., and Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction with the COSMO Model: Description and Sensitivities, Mon. Wea. Rev., 139, 3887–3905, 2011.
Bechini, R. and Chandrasekar, V.: A Semisupervised Robust Hydrometeor Classification Method for Dual-Polarization Radar Applications, J. Atmos. Ocean. Technol., 32, 22–47, 2015.
Bringi, V. N., Thurai, R., and Hannesen, R.: Dual-Polarization Weather Radar Handbook, AMS-Gematronik GmbH, 2007.
Chandrasekar, V., Keranen, R., Lim, S., and D., M.: Recent advances in classification of observations from dual polarization weather radars, Atmos. Res., 119, 9–111, 2013.
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Short summary
In this paper we propose a novel semi-supervised method for hydrometeor classification, which takes into account both the specificities of acquired polarimetric radar measurements and the presumed electromagnetic behavior of different hydrometeor types. The method has been applied on three datasets, each acquired by different C-band radar from the Swiss network, and on two X-band research radar datasets. The obtained classification is found to be of high quality.