The HIROMB-BOOS Model (HBM) has been coupled with the Parallel Data Assimilation Framework PDAF (http://pdaf.awi.de) in order to improve hydrographic forecasts in the North and Baltic Seas. The coupled forecast system assimilates satellite sea surface temperature as well as in situ data of temperature and salinity profiles to initialize forecasts up to 5 days. The assimilation uses an ensemble Kalman filter, which dynamically estimates the uncertainty of the state estimate with an ensemble of model states and applies spatially localized updates to improve the ocean state. The structure of the assimilation system, which can analogously be used to extend other forecast models for data assimilation, is discussed. Applying the assimilation reduces errors of the surface temperature by about 0.2 degrees C.