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

Radenz, Martin; Bühl, Johannes; Seifert, Patric; Griesche, Hannes; Engelmann, Ronny

Clouds are frequently composed of more than one particle population even at the smallest scales. Cloud radar observations frequently contain information on multiple particle species in the observation volume when there are distinct peaks in the Doppler spectrum. Multi-peaked situations are not taken into account by established algorithms, which only use moments of the Doppler spectrum. 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 two case studies, in which the tree structure was used to investigate particle populations in Arctic multilayered mixed-phase clouds, which were observed during the research vessel Polarstern expedition PS106 and the Atmospheric Radiation Measurement Program BAECC campaign.

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Radenz, Martin / Bühl, Johannes / Seifert, Patric / et al: peakTree: a framework for structure-preserving radar Doppler spectra analysis. 2019. Copernicus Publications.

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