A year-long Four-Dimensional Variational (4D-Var) data assimilation experiment, formulated on the physical-space statistical analysis system (PSAS) algorithm, has been applied to the Adriatic Sea for the very first time. High-resolution multi-platform observations were assimilated into the Regional Ocean Modeling System (ROMS) forced by mesoscale atmospheric model ALADIN/HR (Aire Limitée Adaptation dynamique Développement InterNational), including important freshwater river inflows and realistic open boundary conditions for the period between October 2014 and September 2015. The observations included sea surface temperature (SST) measured by satellites, in situ temperature and salinity data measured by various moving (Argo profiling floats, shipborne CTDs, sea glider, towed CTD profiler) and moored platforms, ocean current profiles measured by moored Acoustic Doppler Current Profilers (ADCPs), and 30-minute de-tided surface currents from high-frequency (HF) radars. Three model simulations were integrated: (1) a non-assimilative simulation over a year-long period — baseline simulation; (2) a non-assimilative simulation initiated by the previous assimilation 4-day cycle — background simulation, and (3) a fully assimilative simulation that used all available observations during the 4-day assimilation cycle — analysis simulation. The assimilation significantly improved the modeling system performance, especially in SST, with time average rmse equaling 0.9, 0.7 and 0.5 °C and bias equaling 0.39, 0.15, 0.01 °C for the baseline, background and analysis simulations, respectively. These reductions were mostly achieved during the wintertime outbreaks of a cold and dry bora wind, caused by an underestimation of heat and momentum fluxes by the atmospheric model. Such fine adjustments in the northern and middle Adriatic may be responsible for improved reproduction of dense water generation and the associated Adriatic thermohaline circulation.