Snow is a transient state of water which can store significant amounts of water on the earth surface. The extreme albedo affects the earth's radiation balances and the water content is important for hydrological applications. Therefore, many different remote sensing methods focus on snow parameter retrieval. However, such parameter retrieval often requires significant modeling expertise, knowledge of snow physics and precise field validation data. This talk will focus on the complexity of snow modeling. I will talk over numerous pitfalls which can occur while modeling - not only - snow.
I will present how meteorological information, polarimetric radar data and micro-computertomographic data can be combined to develop a model which can predict the structural anisotropy of snow - layer by layer with cm resolution. The model extends the snow modeling software SNOWPACK developed by WSL-Institute for Snow and Avalanche Research SLF.