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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2019-76
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-76
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 22 Mar 2019

Research article | 22 Mar 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

peakTree: A framework for structure-preserving radar Doppler spectra analysis

Martin Radenz, Johannes Bühl, Patric Seifert, Hannes Griesche, and Ronny Engelmann Martin Radenz et al.
  • Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany

Abstract. Clouds are frequently composed of more than one particle population even at smallest scales. Cloud radar observations contain information on multiple particle species, when there are distinct peaks in the Doppler spectrum. Complex multi-peaked situations are not captured by established algorithms. In this study we propose a new algorithm, that recursively represents the subpeaks as nodes in a binary tree. Using this tree data structure to represent the peaks of a Doppler spectrum it is possible to drop all a-priori assumptions on the number and arrangement of subpeaks. The approach is rigid, unambiguous and can provide a basis for advanced analysis methods. The applicability is briefly demonstrated in a case study, where the tree structure was used to separate two particle populations in an Arctic multi-layered mixed-phase cloud, which was observed during the research vessel Polarstern expedition PS106.

Martin Radenz et al.
Interactive discussion
Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Martin Radenz et al.
Model code and software

peakTree version of Feb2019 M. Radenz, J. Bühl, and P. Seifert https://doi.org/10.5281/zenodo.2577387

Martin Radenz et al.
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Latest update: 26 Jun 2019
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Short summary
Clouds frequently consist of multiple particle species. These particles may differ by phase (ice or liquid) or shape (needles, plates, aggregates, graupel) and thus also by fall velocity. When observed by cloud radars, these particle populations are usually represented by separated peaks in the Doppler spectrum. We separate these peaks and represent each of them as a node in a binary tree. The first application of this data structure helps to overcome deficits of currently available methods.
Clouds frequently consist of multiple particle species. These particles may differ by phase (ice...
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