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Many studies have been conducted on the satellite remote sensing of rainfall, but not on the remote sensing of snowfall. To obtain a global view of snowfall in a timely matter, passive high frequency microwave satellite measurements must be used. Therefore, an accurate algorithm for detecting and retrieving snowfall on a global scale is needed. In developing this algorithm, it is important to account for the snow scattering signature which reduces the upwelling emission signal from the ocean surface observed at the top of the atmosphere. However, the emission due to cloud liquid will increase the upwelling radiation, therefore masking the snow scattering signature. Thus, cloud liquid within snow clouds must be understood. In this study, data from the Cloud Profiling Radar on CloudSat and AMSR-E on Aqua are used to investigate the quantity of cloud liquid for snowfall events. The relationship between cloud liquid and echo top, cloud thickness, and two-meter air temperature is determined. The quantity of cloud liquid present in stratiform and convective snowfall events is also compared. Using snowfall profiles obtained from the reflectivity profiles provided by CloudSat, the masking effect of cloud liquid on the snow scattering signature on vertical and horizontal brightness temperature is determined for snow events with various surface snowfall rates. The masking effect on a parameter designed to reduce the emission signal due to cloud liquid, the polarization corrected temperature, is also tested.