As an ice particle grows by riming its shape is expected to change, resulting in a more spherical particle at the later stages of riming. This conceptual model is at the core of the current ice microphysical schemes and used for dual‐polarization radar observation based classification of hydrometeors. A quantitative relation between riming and shapes of snowflake aggregates, however, has not been established yet. This study aims to derive this relation by using surface‐based precipitation and coinciding dual‐polarization radar observations. The observations were collected during four winter seasons, 49 snowstorms, at University of Helsinki measurement station in Hyytiälä, Finland. Results show that relation between the differential reflectivity and reflectivity‐weighted rime mass fraction is not monotonic and depends on reflectivity‐weighted mean diameter. This behavior can be explained by the opposing effects of riming on dual‐polarization radar observations. Riming increases particle bulk density, which leads to more pronounced dual‐polarization radar signatures. As riming progresses the aspect ratio of snowflake increases slowly until the rime mass fraction value reaches a certainty value after which the aspect ratio increases more rapidly. Finally, coutilization of Ze, Zdr, and Kdp for inferring riming fraction is analyzed.

The melting layer of precipitation has a major impact on remote sensing and telecommunications. However, there is a shortage of observational studies to validate and constrain the melting layer models especially for high‐frequency radar bands. In this paper, we report how multifrequency radar Doppler spectra can be used to retrieve the melting layer attenuation at Ka‐ and W‐bands. The presented analysis is based on identifying Rayleigh scattering regions in radar Doppler spectra measurements where dual‐wavelength spectral ratios can be related to differential attenuation. We show that the estimated attenuation at Ka‐ and W‐bands agrees reasonably well with previously reported studies, but there are indications of differences at higher rain rates. We advocate that this technique can be applied to long‐term observations to advance our knowledge of the melting process. The parameterizations of melting layer attenuation as a function of rain rate and radar reflectivity are also presented.

Dual‐frequency dual‐polarization radar observations of the melting of two ice populations in a stratiform rainfall event are presented. The observed phenomenon occurs as a two‐layer linear depolarization ratio (LDR) signature in a single radar bright band. Doppler spectra observations show that the upper LDR layer is caused by the melting of ice needles, potentially generated by the rime‐splintering process, while the lower one is mainly due to the melting of background ice particles formed at the cloud top. The melting signal of small needles acts as a unique benchmark for detecting the onset of melting and is used to verify the current methods for the identification of melting layer boundaries. The radar‐derived characteristics of the melting layer are found to be dependent on the radar variable and frequency used. The implications of the presented findings for radar‐based studies of precipitation properties in and above the melting layer are also discussed.

Abstract. In stratiform rainfall, the melting layer (ML) is often visible in radar observations as an enhanced reflectivity band, the so-called bright band. Despite the ongoing debate on the exact microphysical processes taking place in the ML and on how they translate into radar measurements, both model simulations and observations indicate that the radar-measured ML properties are influenced by snow microphysical processes that take place above it. There is still, however, a lack of comprehensive observations to link the two. To advance our knowledge of precipitation formation in ice clouds and provide new insights into radar signatures of snow growth processes, we have investigated this link. This study is divided into two parts. Firstly, surface-based snowfall measurements are used to develop a new method for identifying rimed and unrimed snow from X- and Ka-band Doppler radar observations. Secondly, this classification is used in combination with multifrequency and dual-polarization radar observations collected during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) experiment in 2014 to investigate the impact of precipitation intensity, aggregation, riming and dendritic growth on the ML properties. The results show that the radar-observed ML properties are highly related to the precipitation intensity. The previously reported bright band “sagging” is mainly connected to the increase in precipitation intensity. Ice particle riming plays a secondary role. In moderate to heavy rainfall, riming may cause additional bright band sagging, while in light precipitation the sagging is associated with unrimed snow. The correlation between ML properties and dual-polarization radar signatures in the snow region above appears to be arising through the connection of the radar signatures and ML properties to the precipitation intensity. In addition to advancing our knowledge of the link between ML properties and snow processes, the presented analysis demonstrates how multifrequency Doppler radar observations can be used to get a more detailed view of cloud processes and establish a link to precipitation formation.

Abstract. In stratiform rainfall, the melting layer is often visible in radar observations as an enhanced reflectivity band, the so-called bright band. Despite the ongoing debate on the exact microphysical processes taking place in the melting layer and on how they translate into radar measurements, both model simulations and observations indicate that the radar-measured melting layer properties are influenced by snow microphysical processes that take place above it. There is still, however, a lack of comprehensive observations to link the two. To advance our knowledge of precipitation formation in ice clouds and provide an additional constraint on the retrieval of ice cloud microphysical properties, we have investigated this link. This study is divided into two parts. Firstly, surface-based snowfall measurements are used to devise a method for classifying rimed and unrimed snow from X- and Ka-band Doppler radar observations. In the second part, this classification is used in combination with multi-frequency and dual-polarization radar observations to investigate the impact of precipitation intensity, aggregation, riming, and dendritic growth on melting layer properties. The radar-observed melting layer characteristics show strong dependence on precipitation intensity as well as detectable differences between unrimed and rimed snow. This study is based on the data collected during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) experiment, that took place in 2014 in Hyytiala, Finland.