Aiming to provide sea surface salinity (SSS) maps with a spatiotemporal averaged accuracy of 0.1 psu (practical salinity units), the Soil Moisture and Ocean Salinity (SMOS) community is increasingly focusing on the determination of a robust inversion scheme to enable SSS retrieval from L-band brightness temperature data. In the framework of the Synergetic Aspects and Auxiliary Data Concepts for Sea Surface Salinity Measurements from Space project, efforts have been oriented toward a quantitative analysis of SSS retrieval using different auxiliary data sets. This paper aims to contribute to the assessment of the SMOS salinity retrieval error budget in view of the upcoming SMOS mission ground segment development. Aiming to do that, different models and auxiliary data to simulate and invert the brightness temperature data have been used. An estimation of the different auxiliary parameters' influence has been performed to quantitatively predict at what extent it is reasonable to expect to retrieve salinity once the brightness temperatures are directly measured by the sensor. Statistical distributions of the spatiotemporal averaged errors are provided.