Snow on sea ice is a crucial component of the polar cryosphere. It insulates sea ice against atmospheric processes and influences the net shortwave radiation flux at and within the sea ice with a number of implications for sea-ice physics (ice growth and melt) as well as biota (availability of shortwave radiation). The formation of snow ice and/or superimposed ice is hypothesized to play a considerable role for the Antarctic sea-ice mass balance. Hence, accurate knowledge of the snow depth on sea ice is an asset to accurately model ocean–ice–atmosphere heat fluxes, and to derive the ice thickness using satellite altimetry. However, while satellite microwave radiometry allows us to obtain circum-Antarctic snow-depth estimates the accuracy of this product is still under debate. A case study carried out recently, based on observations during the Sea Ice Mass Balance in the Antarctic (SIMBA) ice drift station in the Bellingshausen Sea, Antarctica, in 2007, confirmed findings of the Antarctic Remote Ice Sensing Experiment (ARISE) in East Antarctica: snow-depth records based on Advanced Microwave Scanning Radiometer (AMSR-E) data tend to considerable underestimations over rough sea ice. In this study we aim to elaborate on the results of this case study. AMSR-E snow depths will be compared with in situ observations carried out on the ice along surface profiles and from aboard the ship according to the ASPeCt protocol during SIMBA and during two other cruises which took place in the Weddell Sea: Ice Station POLarstern (ISPOL) and Winter Weddell Outflow Study (WWOS). Coincident C-band (Envisat ASAR and RADARSAT-1 SAR) and Ku-band (QuikSCAT) radar backscatter data will be used in concert with the in situ observations to obtain information about the spatial distribution of sea-ice types and to obtain an estimate of the surface roughness pattern. These will be examined together with the AMSR-E snow-depth distribution. Based on the results of this investigation and the results of the comparison between in situ and AMSR-E snow-depth data we aim to provide information about the spatio-temporal distribution of potential snow-depth underestimation by AMSR-E.