Measuring snowfall properties with the Video In Situ Snowfall Sensor during MOSAiC

Snow is an essential component of the climate system impacting surface albedo, glaciers, sea ice, freshwater storage, and cloud lifetime. Even though we do not know the exact pathways through which ice, liquid, cloud dynamics, and aerosols are interacting in clouds while forming snowfall, the involved processes can be identified by their fingerprints on snow particles. The general shape of individual crystals (dendritic, columns, plates) depends on the temperature and moisture conditions during growth from water vapor deposition. Aggregation can be identified when multiple individual particles are combined into a snowflake. Riming describes the freezing of cloud droplets onto the snow particle and can eventually form graupel. In order to exploit these unique fingerprints of cloud microphysical processes, optical observations are required.

The Video In Situ Snowfall Sensor (VISSS) was specifically developed for the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) campaign to determine particle shape and particle size distributions. Different to other sensors, the VISSS minimizes uncertainties by combining two-dimensional high-resolution images with a large measurement volume and a design limiting the impact of wind. Here, we show first results from the MOSAiC campaign and present examples for synergy effects that can be obtained by combining radar and VISSS measurements.