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We have analyzed the dependence of the calculated magnitudes of buoyancy fluxes at the ocean surface on the various sources of information used about salinity based on the example of 2014 with anomalous convection in the Labrador Sea. In particular, we have used the NCEP CFSv2 reanalysis, Aquarius satellite data, and ISAS-15 dataset based on the Argo network of profiling floats. In boreal winter, NCEP CFSv2 shows the highest salinity in subequatorial and tropical latitudes and in the eastern Indian and western Pacific Ocean as compared to other datasets. In boreal summer, the salinity according to the reanalysis is the lowest in the Bay of Bengal. Significant discrepancies between CFSv2 and ISAS-15 are also revealed in the subpolar latitudes of the Northern/Southern Hemisphere in boreal/austral winter. Negative biases in salinity correspond to positive biases in the density flux (which is the inverse of the buoyancy flux) in subpolar latitudes, while this is not necessarily the case in other regions. It is shown that the mesoscale variability of salinity exerts an insignificant effect on density fluxes (up to 1% of mean values) compared to the effect of the various salinity datasets used (up to 10% of the mean values), the largest differences being revealed in low and middle latitudes, where the impact of precipitation is high. The obtained data on the role of nonlinear effects related to mesoscale variability in the salinity represent a methodological basis for studying the long-term variability of surface density fluxes and surface water transformation, using monthly mean salinity. [ABSTRACT FROM AUTHOR]