Abstract
Abstract. 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.
Highlights
The characterization of mixed-phase clouds and associated microphysical processes poses a challenge to experimentalists, and these processes are still not well represented in general circulation models (Fan et al, 2011)
When multiple particle populations are present in the observed volume, they are frequently represented as distinct peaks in the Doppler spectrum (e.g., Shupe et al, 2004; Luke et al, 2010; Verlinde et al, 2013; Yu et al, 2014; Kalesse et al, 2016; Kollias et al, 2016)
We proposed a binary tree structure for individual peaks of a multi-peaked cloud radar Doppler spectrum
Summary
The characterization of mixed-phase clouds and associated microphysical processes poses a challenge to experimentalists, and these processes are still not well represented in general circulation models (Fan et al, 2011). In a further step, Oue et al (2018), using the microARSCL algorithm (Kollias et al, 2007b; Luke et al, 2008), allow a primary peak to be split into two subpeaks. They constrain the structure by assuming the left peak (faster falling peak) to have a higher reflectivity. A noise-floor-separated secondary peak is possible, but this one is assumed to be mono-modal Such strong constraints may be justified for short periods at single geographic locations but are not suitable for a general approach.
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