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Publisher: Göttingen : Copernicus GmbH × Subject: Doppler radar ×

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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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    Can VHF radars at polar latitudes measure mean vertical winds in the presence of PMSE?
    (Göttingen : Copernicus GmbH, 2019) Gudadze, N.; Stober, G.; Chau, J.L.
    Mean vertical velocity measurements obtained from radars at polar latitudes using polar mesosphere summer echoes (PMSEs) as an inert tracer have been considered to be non-representative of the mean vertical winds over the last couple of decades. We used PMSEs observed with the Middle Atmosphere Alomar Radar System (MAARSY) over Andøya, Norway (69.30°N, 16.04°E), during summers of 2016 and 2017 to derive mean vertical winds in the upper mesosphere. The 3-D vector wind components (zonal, meridional and vertical) are based on a Doppler beam swinging experiment using five beam directions (one vertical and four oblique). The 3-D wind components are computed using a recently developed wind retrieval technique. The method includes full non-linear error propagation, spatial and temporal regularisation, and beam pointing corrections and angular pointing uncertainties. Measurement uncertainties are used as weights to obtain seasonal weighted averages and characterise seasonal mean vertical velocities. Weighted average values of vertical velocities reveal a weak upward behaviour at altitudes ∼ 84-87 km after eliminating the influence of the speed of falling ice. At the same time, a sharp decrease (increase) in the mean vertical velocities at the lower (upper) edges of the summer mean altitude profile, which are attributed to the sampling issues of the PMSE due to disappearance of the target corresponding to the certain regions of motions and temperatures, prevails. Thus the mean vertical velocities can be biased downwards at the lower edge, and the mean vertical velocities can be biased upwards at the upper edge, while at the main central region the obtained mean vertical velocities are consistent with expected upward values of mean vertical winds after considering ice particle sedimentation. © 2019 Author(s). This work is distributed under the Creative Commons Attribution 4.0 License.