A new method based on modified self-organizing maps is presented for the reconstruction of deep ocean current velocities from surface information provided by satellites. This method takes advantage of local correlations in the data-space to improve the accuracy of the reconstructed deep velocities. No assumptions regarding the s

tructure of the water column, nor the underlying dynamics of the flow field, are made. Using satellite observations of surface velocity, sea-surface height and sea-surface temperature, as well as observations of the deep current velocity from autonomous Argo floats to train the map, we are able to reconstruct realistic high-resolution velocity fields at a depth of 1000 m. Validation reveals promising results, with a speed root mean squared error of ∼2.8 cm/s, morethan a factor of two smaller than competing methods, and direction errors consistently smaller than 30°. Finally, we discuss the merits and shortcomings of this methodology