Precipitation structures are easy to detect, however, the mesoscale atmospheric processes which they reflect are challenging to understand in Polar Regions and hard to model numerically. Currently, the spatial distribution of precipitation can be tracked at the resolution of minutes and seconds. For this purpose, the researchers at the Ukrainian Antarctic Akademik Vernadsky station employ several near-ground measurement systems and the Micro Rain Radar for remote vertical measurements. Measurements show stochastic precipitation variability caused by turbulence, precipitation bands related to the atmospheric processes of its formation, phase transition (melting) zones, and wind shears. The time scale of bands in the stratiform precipitation typically varied in the range of 5—15 minutes and corresponded to the 2—15 km spatial scale of atmospheric circulations according to the modeled parameters of the atmosphere. The Polar Weather Research and Forecast (Polar WRF) model was used to reveal the general atmospheric conditions. We also tested and evaluated its ability to reproduce small structures. A simple method based on typical model variables is proposed to identify the precipitation melting layer in the simulation data, similar to that determined by radars. The results were satisfyingly consistent with the position of the 0 °C isotherm in the model and with the radar measurements. In addition, the method highlighted supercooled mixed-phase precipitation. Modeling showed good results for large-scale processes like atmospheric fronts and general air mass features in the case study. However, even at the 1 km resolution the simulation reproduced thin mesoscale precipitation features smoothly, which sometimes looks unrealistic. As for other precipitation peculiarities, like band inclination, melting layer position, and mixed-phase zones, the Polar WRF model demonstrates high consistency with observations. The model can describe the atmospheric conditions except for the investigation of precipitation-initiating mechanisms, which still is a challenge for modeling at a small scale.