The PhD student will conduct independent research as part of the drOPS (clouD and pRecipitation
Observations for Process Studies) group at LIM for the Evaluating Microphysical Pathways Of Midlatitude
Snow Formation (EMPOS) project. The candidate will develop and apply machine learning data products for
the Video In Situ Snowfall Sensor (VISSS) to quantify riming and aggregation from in situ observations. The
VISSS measurement uncertainties will be quantified. The required data set will be collected during a field
campaign at Hyytiälä, Finland. Together with a PhD student of the collaboration partner C. Hoose at KIT, the
observations will be compared with the ICON (Icosahedral Nonhydrostatic) model using the advanced P3
(Predicted Particle Properties) microphysics scheme, which has a novel approach to the treatment of rimed
particles. The goal is to evaluate and improve the snowfall simulation in ICON. Results will be published in
peer-reviewed journals and presented at international conferences.