This paper aims to separate different snow regions over the terrestrial ice sheets based on their measured microwave signatures. It takes advantage of coregistered data from passive and active sensors on the Environmental Satellite (Envisat) to directly derive a snow facies indicator in a point-by-point basis. This paper represents the first attempt of this kind in exploiting nadir-viewing and dual-frequency data from both altimeter and radiometer sensors. The approach is based on a clustering method. Such representation of the data by means of fewer clusters necessarily loses fine details but achieves simplification in geographical representation and eases the description of the condition of the ice sheets in 2004. Our approach broadens the description of the snow pack by taking into account characteristics such as surface roughness, grain size, stratification, and snowmelt effects, whereas the latter has often solely been considered in most previous work. Such partition of the ice sheets might help to better understand relationships between microwave signatures and snow morphology. It could also be useful for estimating elevation uncertainty in altimeter data, which, in turn, is essential to correctly interpret the significance of the rates of elevation change in a changing climate and to convert elevation change to snow mass change.