Recently published studies of triple-frequency radar observations of snowfall have demonstrated that naturally occurring snowflakes exhibit scattering signatures that are in some cases consistent with spheroidal particle models and in others can only be explained by complex aggregates. Until recently, no in situ observations have been available to investigate links between microphysical snowfall properties and their scattering properties. In this study, we investigate for the first time relations between collocated ground-based triple-frequency observations with in situ measurements of snowfall at the ground. The three analyzed snowfall cases obtained during a recent field campaign in Finland cover light to moderate snowfall rates with transitions from heavily rimed snow to open-structured, low-density snowflakes. The observed triple-frequency signatures agree well with the previously published findings from airborne radar observations. A rich spatiotemporal structure of triple-frequency observations throughout the cloud is observed during the three cases, which often seems to be related to riming and aggregation zones within the cloud. The comparison of triple-frequency signatures from the lowest altitudes with the ground-based in situ measurements reveals that in the presence of large (>5 mm) snow aggregates, a bending away in the triple-frequency space from the curve of classical spheroid scattering models is always observed. Rimed particles appear along an almost horizontal line in the triple-frequency space, which was not observed before. Overall, the three case studies indicate a close connection of triple-frequency signatures and snow particle structure, bulk snowfall density, and characteristic size of the particle size distribution.

The capability to detect the state of snowflake riming reliably from remote measurements would greatly expand the understanding of its global role in cloud‐precipitation processes. To investigate the ability of multifrequency radars to detect riming, a three‐dimensional model of snowflake growth was used to generate simulated aggregate and crystal snowflakes with various degrees of riming. Three different growth scenarios, representing different temporal relationships between aggregation and riming, were formulated. The discrete dipole approximation was then used to compute the radar backscattering properties of the snowflakes at frequencies of 9.7, 13.6, 35.6, and 94 GHz. In two of the three growth scenarios, the rimed snowflakes exhibit large differences between the backscattering cross sections of the detailed three‐dimensional models and the equivalent homogeneous spheroidal models, similarly to earlier results for unrimed snowflakes. When three frequencies are used simultaneously, riming appears to be detectable in a robust manner across all three scenarios. In spite of the differences in backscattering cross sections, the triple‐frequency signatures of heavily rimed particles resemble those of the homogeneous spheroids, thus explaining earlier observational results that were compatible with such spheroids.

The sensitivity of radar backscattering cross sections on different snowflake shapes is studied at C, Ku, Ka, and W bands. Snowflakes are simulated using two complex shape models, namely, fractal and aggregate, and a soft spheroid model. The models are tuned to emulate physical properties of real snowflakes, that is, the mass–size relation and aspect ratio. It is found that for particle sizes up to 5 mm and for frequencies from 5 to 35 GHz, there is a good agreement in the backscattering cross section for all models. For larger snowflakes at the Ka band, it is found that the spheroid model underestimates the backscattering cross sections by a factor of 10, and at W band by a factor of 50–100. Furthermore, there is a noticeable difference between spheroid and complex shape models in the linear depolarization ratios for all frequencies and particle sizes.

Key Points:• The triple-frequency radar signature of aggregate snowflakes was studied • The signature is not sensitive to the type of ice crystals in the aggregate • The size of the constituent crystals does have a measurable effect Supporting Information:• Readme • Table S1 Correspondence to: Abstract A large data set of volume element models of aggregate snowflakes was created, building the snowflakes from various models of ice crystals found in the atmosphere: dendrites, needles, plates, and bullet rosettes, as well as spheroidal crystals for comparison. Several different sizes for the constituent crystals were also used. The radar backscattering cross sections of the snowflakes were computed from the models using the discrete dipole approximation (DDA) at 13.6 GHz (K u band), 35.6 GHz (K a band) and 94.0 GHz (W band), and the effects of the choice of crystal model and size on the K u ∕K a band and K a ∕W band dual-wavelength ratios (DWR) was investigated. It was found that the aggregate DWRs were very similar for all naturally occurring ice crystal types investigated in this study. This implies that the choice of crystal type is at most of secondary importance in the forward model of scattering used for snowfall retrievals but also, conversely, that the identification of the crystal type from triple-frequency observations is likely to be difficult. In contrast, the size of the constituent ice crystals does have a nonnegligible impact on the triple-frequency signatures. Additionally, it was found that the triple-frequency signatures found in some experimental data, resembling those resulting from spheroidal model snowflakes, cannot be reproduced using the aggregates with any of the crystal types that were investigated. This suggests that besides aggregation, other mechanisms of snowflake formation from ice crystals must be considered in snowfall retrieval algorithms.