Evaluating Microphysical Pathways Of midlatitude Snow formation (EMPOS)

• Applicants: Professorin Dr. Corinna Hoose; Dr. Maximilian Maahn
• Subject Area: Atmospheric Science
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 516261703

Precipitation is a major yet poorly understood component of our climate system. The exact pathways through which ice crystals, liquid water, cloud dynamics, and aerosol particles are interacting during precipitation formation are not well understood. As most precipitation is formed in ice-containing clouds anywhere except over the subtropical Oceans, snowfall formation processes are highly relevant not only in polar but also in mid-latitude regions: during snowfall formation, vapor depositional growth leads to innumerable crystal shapes depending on temperature, humidity, and their turbulent fluctuations. Aggregation combines individual crystals to complex snowflakes. Riming describes the freezing of small droplets to the ice crystals so that they gain mass rapidly. In other words, the snow particle shape - if observed before the particle melts into a raindrop - is a fingerprint of the dominating process pathways during snowfall formation. In EMPOS, we propose to use these fingerprints for quantifying how the various snowfall formation processes contribute to total precipitation with respect to mass or frequency of occurrence. For this, we will advance the data products of the innovative Video In Situ Snowfall Sensor (VISSS) to quantify riming and aggregation from observations during a dedicated measurement campaign in Hyytiälä, Finland. The observations will be compared to the ICON model using the advanced P3 (Predicted Particle Properties) microphysics scheme that has radically different approaches to the treatment of rimed particles. This combined observational and modeling project will allow quantifying how the individual cloud processes are involved in snowfall formation in terms of frequency of occurrence and total snow mass. Further, we will analyze these cloud processes as a function of macrophysical cloud properties such as cloud depth and synoptic forcing. Based on comparisons of model and observations using both case studies and longer periods, we will evaluate and improve snowfall simulation in ICON in the standard two-moment scheme and in the P3 microphysical scheme.

• DFG Programme: Research Grants