We generated a large number (105’000) of aggregates composed of various monomer types and sizes using an aggregation model. Combined with hydrodynamic theory, we derived ice particle properties such as mass, projected area, and terminal velocity as a function of monomer number and size. This particle ensemble allows us to study the relation of particle properties with a high level of detail which is often not provided by in-situ measurements. The ice particle properties change rather smoothly with monomer number. We find very little differences in all particle properties between monomers and aggregates at sizes below 1 mm which is in contrast to many microphysics schemes. The impact of the monomer type on the particle properties decreases with increasing monomer number. Whether e.g., the terminal velocity of an aggregate is larger or smaller than an equal-size monomer, depends mostly on the monomer type. We fitted commonly used power laws as well as Atlas-type relations, which represent the saturation of the terminal velocity at larger sizes (terminal velocity asymptotically approaching a limiting value), to the dataset and tested the impact of incorporating different levels of complexity with idealized simulations using a 1D Lagrangian super-particle model. These simulations indicate that it is sufficient to represent the monomer number dependency of ice particle properties with only two categories (monomers and aggregates). The incorporation of the saturation velocity at larger sizes is found to be important to avoid an overestimation of self-aggregation of larger snowflakes.

Understanding which microphysical processes are dominant while ice particles pass through the melting layer is essential for precipitation prediction by microphysics schemes and precipitation estimates by remote sensing. Comparing the reflectivity flux at the top and bottom of the melting layer reveals the overall effect of the microphysical processes occurring within the melting layer on the particle population. If the reflectivity flux increases more than expected due to the change in the dielectric factor, growth processes dominate. In contrast, a weaker increase in reflectivity flux indicates that shrinking processes dominate. However, inference of growth or shrinking dominance from the increase in reflectivity flux is only possible if other influences (e.g., vertical wind speed) are negligible or corrected for. By analyzing radar spectra and multi-frequency observations, we correct the reflectivity fluxes for vertical wind speed and categorize the height profiles by the riming degree at the melting layer top. Our statistical analysis shows the slight dominance of growth processes for unrimed and a clearer dominance of shrinking processes for rimed profiles. The reflectivity flux profiles within the melting layer indicate that the difference between unrimed and rimed profiles arises mainly in the upper half of the melting layer, where the melting fraction increases the strongest. We further narrow down which processes might be most important to explain the observed signature by analyzing additional radar variables. We suggest that whether the particle population is overall growing or shrinking depends on the relative importance of aggregation and collisional breakup of melting particles.

Shallow mixed-phase clouds (MPCs) occur extensively in the Arctic, and are known to play a key role for the energy budget. While their characteristic structure is nowadays well understood, the significance of different precipitation-formation processes, such as aggregation and riming, is still unclear. Using a 3-year dataset of vertically-pointing W-band cloud radar and K-band Micro Rain Radar (MRR) observations from Ny-Ålesund, Svalbard, we statistically assess the relevance of aggregation in Arctic low-level MPCs. Combining radar observations with thermodynamic profiling, we find that larger snowflakes (mass median diameter above 1 mm) are predominantly produced in shallow MPCs whose mixed-phase layer is at temperatures between -15 and -10°C. This coincides with the temperature regime known for favoring aggregation due to growth and subsequent mechanical entanglement of dendritic crystals. Doppler velocity information confirms that these signatures are likely due to enhanced ice particle growth by aggregation. Signatures indicative of enhanced aggregation are however not distributed uniformly across the cloud deck, and only observed in limited regions, suggesting a link with dynamical effects. Low Doppler velocity values further indicate that significant riming of large particles is unlikely at temperatures below -5°C. Surprisingly, we find no evidence of enhanced aggregation at temperatures above -5°C, as is typically observed in deeper cloud systems. Possible reasons are discussed, likely connected to the ice habits that form above -10°C, increased riming, and lack of already aggregated particles precipitating from higher altitudes.