Characterising the occurrence of monomodal and multimodal ice hydrometeor populations and their fall speeds in midlatitude frontal ice clouds using radar Doppler spectra

Abstract. Multimodality in vertically pointing radar Doppler spectra is frequently observed in stratiform clouds, but understanding the microphysical processes causing these signatures remains a challenge. In this study, we utilise Ka-band radar Doppler spectra from 23 deep stratiform clouds observed over Chilbolton, UK. We apply a peak finding algorithm to identify spectral reflectivity peaks in the Doppler spectra, which can be used to infer the presence of distinct coexisting ice particle populations, such as pristine crystals mixed with aggregate snowflakes. Using these results, we can provide the first quantitative estimate for the distribution of multimodal spectra with temperature. There are two clear temperature regimes where the occurrence of multimodal spectra increases sharply, indicating production of new particles; these are between −8 ^oC and −3 ^oC, which we attribute to rime splintering, and between −18 ^oC and −13 ^oC, where the mechanism responsible for producing multimodal spectra is unclear.

The peak finding algorithm also returns the velocities associated with the peaks in spectral reflectivity, which allows us to analyse the distribution of velocity with temperature for primary and secondary particle populations. We show evidence that primary populations from monomodal spectra experience a significant reduction in fall velocity at −13 ^oC. We show evidence that this feature is governed by the primary population; that is, falling particles are slowing down. Dendritic growth is favoured near this temperature, and we therefore hypothesise that particles such as polycrystals and aggregates, which form in colder cloud layers, precipitate to this level, form dendritic branches, and therefore experience increased air resistance.