Articles | Volume 11, issue 8
https://doi.org/10.5194/amt-11-4847-2018
https://doi.org/10.5194/amt-11-4847-2018
Research article
 | 
22 Aug 2018
Research article |  | 22 Aug 2018

Unraveling hydrometeor mixtures in polarimetric radar measurements

Nikola Besic, Josué Gehring, Christophe Praz, 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. Tech., 52, 2328–2344, 2013. a
Balakrishnan, N. and Zrnic, D. S.: Estimation of Rain and Hail Rates in Mixed-Phase Precipitation, J. Atmos. Sci., 47, 565–583, 1990. a, b
Bechini, R. and Chandrasekar, V.: A Semisupervised Robust Hydrometeor Classification Method for Dual-Polarization Radar Applications, J. Atmos. Ocean. Tech., 32, 22–47, 2015. a
Besic, N., Vasile, G., Chanussot, J., and Stankovic, S.: Polarimetric Incoherent Target Decomposition by Means of Independent Component Analysis, IEEE T. Geosci. Remote, 53, 1236–1247, 2015. a
Besic, N., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Hydrometeor classification through statistical clustering of polarimetric radar measurements: a semi-supervised approach, Atmos. Meas. Tech., 9, 4425–4445, https://doi.org/10.5194/amt-9-4425-2016, 2016. a, b, c, d, e, f, g, h, i, j, k
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Short summary
In this paper we propose an innovative approach for hydrometeor de-mixing, i.e., to identify and quantify the presence of mixtures of different hydrometeor types in a radar sampling volume. It is a bin-based approach, inspired by conventional decomposition methods and evaluated using C- and X-band radar measurements compared with synchronous ground observations. The paper also investigates the potential influence of incoherency in the backscattering from hydrometeor mixtures in a radar volume.