We assess the impact of multi-satellite altimetry data on the representation of circulations down to submesoscales of the order of 1 km. Sub-km horizontal grid spacing is increasingly used in regional forecasting models to resolve submesoscale flows. To ensure a positive impact of satellite altimetry data in a model of sub-km grid spacing, we need to deal with a set of particular difficulties. Among those difficulties are the limited footprint size of altimetry measurement, dynamical imbalance, spatial localization and temporal intermittency, and others. Leveraging a real-time multiscale three-dimensional variational data assimilation (MS-3DVAR) and forecasting system, which supports the Salinity Processes in the Upper Ocean Regional Study (SPURS) field campaign in the North Atlantic Ocean in 2012-2013 (SPURS-1) and the eastern Tropical Pacific ocean in 2016-2017 (SPURS-2), and the SPURS multi-scale observing network, we illustrate those difficulties, address methodologies and formulations to deal with those difficulties, and demonstrate positive impacts of multi-satellite altimetry on the prediction of submesoscale flows.