Presented at the 2020 Ocean Sciences MeetingLand-sea linkage through river discharges represents a critical branch of the global water cycle, influencing ocean dynamics, marine ecosystem, and biogeochemistry. Due to the lack of a systematic global measurement network for river discharges, global ocean model and assimilation systems have typically used estimates of climatological river discharges to force the ocean models. This limitation affects the simulated non-seasonal salinity variation near river plumes and undermines their usefulness for ecosystem and biogeochemical studies. Satellite salinity measurements revealed large interannual variation of sea surface salinity (SSS) in large river plume regions that are linked to interannual variation of river discharges. Recently, a daily-varying discharge forcing dataset JRA55-do was developed to force ocean models. Here we use this global daily river discharge dataset to force a global MIT ocean general circulation model with spatial resolutions of approximately 13-33 km. We contrast this model simulation with that forced by the JRA55-do derived seasonal climatology of global river discharges (but with the same atmospheric forcings) to isolate the impacts of non-seasonal river discharges, focusing on SSS near large river plumes. Our analysis results suggest that non-seasonal variability in discharges has detectable impacts on SSS near major river plumes that exceed satellite SSS observational uncertainties. Moreover, the inclusion of non-seasonal river discharges improves the comparison of the model SSS with satellite measurements near some of the major rivers on interannual timescales, and in some cases, for sub-seasonal time scales as well.