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The friction velocity is estimated from image sequences of a marine Radar, which operates at grazing incidence with X-band at horizontal polarization in transmit and receive. Therefore, radar image sequences are analyzed in space and time. The direction of the friction velocity is extracted from streak like features visible in the image resulting from the temporal integrated radar image sequence. The orientation of these streaks are determined by derivation of local gradients of the radar images. The magnitude of the friction velocity is derived from the measured normalized radar cross section by a geophysical model function (GMF), which is parameterized by training of a Neural Network. For further improvement of the GMF the radar retrieved signal to noise ratio, which is strongly related to the significant wave height, is taken into account. The methodology is validated at FINO-I, a research platform in the North Sea, were various meteorological and oceanographical parameters are measured on an operational basis. The radar retrieved friction velocities are compared to in-situ wind directions as well as to the friction velocities estimated from in situ measurements using the TOGA COARE formulation. The comparison resulted in a standard deviation of 13deg for wind direction and 0.41 ms-1 for the magnitude of the friction velocity. In contrast to traditional measurements the retrieval of friction velocity from marine radars is free of platform induced effects, e.g., turbulence, and can be used from moving platforms.