It is accepted that the best way to monitor sea surface salinity (SSS) on a global basis is by means of L-band radiometry. However, the measured sea surface brightness temperature (TB) depends not only on the SSS but also on the sea surface temperature (SST) and, more importantly, on the sea state, which is usually parameterized in terms of the 10-m-height wind speed (U10) or the significant wave height. It has been recently proposed that the mean-square slope (mss) derived from global navigation satellite system (GNSS) signals reflected by the sea surface could be a potentially appropriate sea-state descriptor and could be used to make the necessary sea state TB corrections to improve the SSS estimates. This paper presents a preliminary error analysis of the use of reflected GNSS signals for the sea roughness correction and was performed to support the European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) mission; the orbit and parameters for the SMOS instrument were assumed. The accuracy requirement for the retrieved SSS is 0.1 practical salinity units after monthly averaging over 2◦ × 2◦ boxes. In this paper, potential improvements in salinity estimation are hampered mainly by the coarse sampling and by the requirements of the retrieval algorithm, particularly the need for a semiempirical model that relates TB and mss.