Towards the connection between snow microphysics and melting layer: insights from multifrequency and dual-polarization radar observations during BAECC

Abstract

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.