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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

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https://doi.org/10.5194/amt-2018-58
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
06 Mar 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).
Unraveling hydrometeor mixtures in polarimetric radar measurements
Nikola Besic1,2, Josué Gehring1, Christophe Praz1, Jordi Figueras i Ventura2, Jacopo Grazioli2, Marco Gabella2, Urs Germann2, and Alexis Berne1 1Environmental Remote Sensing Laboratory (LTE), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
2Radar, Satellite, Nowcasting Department (MDR), MeteoSwiss, Locarno-Monti, Switzerland
Abstract. Radar-based hydrometeor classification typically comes down to determining the dominant type of hydrometeor populating a radar sampling volume. In this paper we address the subsequent problem of inferring the secondary hydrometeor types present in a volume – the issue of hydrometeor de-mixing. The presented study relies on the semi-supervised hydrometeor classification proposed by Besic et al. (2016), but nevertheless results in solutions and conclusions of a more general character and applicability. In the first part, dominantly marked by synthesis, a bin-based de-mixing approach is proposed, inspired by the conventional coherent and linear decomposition methods widely employed across different remote sensing disciplines. Intrinsically related to the concept of entropy, introduced in the context of the radar hydrometeor classification in Besic et al. (2016), the proposed method, based on the hypothesis of coherency in backscattering, estimates the proportions of different hydrometeor types in a given radar sampling volume, without considering the wider spatial context. Plausibility and performances of the method are evaluated using C and X band radar measurements, compared with hydrometeor properties derived from a Multi Angle Snowflake Camera instrument. In the second part, we examine the influence of the potential incoherency in the backscattering from different hydrometeors populating a radar sampling volume. This part, consists of adapting and testing the techniques commonly used in conventional incoherent decomposition methods to the context of weather radar polarimetry. The impact of the incoherence is found to be limited, justifying the hypothesis of coherency even in a case of mixed volumes, and confirming the applicability of the proposed bin-based approach.
Citation: Besic, N., Gehring, J., Praz, C., Figueras i Ventura, J., Grazioli, J., Gabella, M., Germann, U., and Berne, A.: Unraveling hydrometeor mixtures in polarimetric radar measurements, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2018-58, in review, 2018.
Nikola Besic et al.
Nikola Besic et al.
Nikola Besic et al.

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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.
In this paper we propose an innovative approach for hydrometeor de-mixing, i.e. to identify and...
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