Detection of Multi-Modal Doppler Spectra – Part 2: Evaluation of the Detection Algorithm and Exploring Characteristics of Multi-modal Spectra Using a Long-term Dataset

In this paper, we process three years of vertically pointing Ka-band radar spectral data according to the methodology described and established in Part 1 (Wugofski et al., 2025). Across three years of data, we demonstrate that the detection algorithm is successful in identifying multi-modal spectra, with 89.6 % of detected events verifying. Beyond the verification, we explore other characteristics of the detected events such as the height, depth, and temperature of the layers containing secondary modes. Reanalysis data from ERA5 was used to gain additional context to the environmental conditions associated with the detected events. By connecting temperatures from ERA5 with the detected layers, we assess the potential for these events to be associated with common microphysical processes such as growth of columns or plates, Hallett–Mossop rime splintering, dendritic growth, and primary ice nucleation. We further explore the potential microphysical processes revealed by the multi-modal spectra using spectrally integrated linear depolarization ratio to determine if the secondary mode may comprise ice crystals that can produce such a signal. Of the cases with a detected enhanced LDR signal, >64.1 % of those occurred in a layer with a mean temperature consistent with columnar ice or Hallett–Mossop rime splintering. Finally, three cases are investigated in more detail to illustrate the variety of events detected by the algorithm.