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search.filters.applied.f.access: openAccess × Type: Text × Publisher: Göttingen : Copernicus GmbH × Subject: algorithm × WGL Institute: TROPOS ×

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    PeakTree: A framework for structure-preserving radar Doppler spectra analysis
    (Göttingen : Copernicus GmbH, 2019) Radenz, M.; Bühl, J.; Seifert, P.; Griesche, H.; Engelmann, R.
    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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    Combining cloud radar and radar wind profiler for a value added estimate of vertical air motion and particle terminal velocity within clouds
    (Göttingen : Copernicus GmbH, 2018) Radenz, M.; Bühl, J.; Lehmann, V.; Görsdorf, U.; Leinweber, R.
    Vertical-stare observations from a 482MHz radar wind profiler and a 35GHz cloud radar are combined on the level of individual Doppler spectra to measure vertical air motions in clear air, clouds and precipitation. For this purpose, a separation algorithm is proposed to remove the influence of falling particles from the wind profiler Doppler spectra and to calculate the terminal fall velocity of hydrometeors. The remaining error of both vertical air motion and terminal fall velocity is estimated to be better than 0.1ms-1 using numerical simulations. This combination of instruments allows direct measurements of in-cloud vertical air velocity and particle terminal fall velocity by means of ground-based remote sensing. The possibility of providing a profile every 10s with a height resolution of < 100m allows further insight into the process scale of in-cloud dynamics. The results of the separation algorithm are illustrated by two case studies, the first covering a deep frontal cloud and the second featuring a shallow mixed-phase cloud.