| Summary: | In this paper, the statistical properties of the mean flow reconstruction using Lagrangian data are studied, considering the classical "binning" approach based on space-time averaging of finite difference velocity estimates. The work is performed numerically, using as the test flow a solution from a high resolution MICOM simulation of the North Atlantic. A set of trajectories are computed, simulating the motion of surface drifters initially launched on a regular 1 o \Theta 1 o array, transmitting positions every \Deltat = 12 hours, and analyzed over approximately 2 years of the simulation. The drifter distribution in time is influenced by the Ekman flow, resulting in maximum data concentration in the subtropical convergence regions and minimum concentration in the upwelling regions. Pseudo-Eulerian averages U pE , computed from Lagrangian data, are compared to "true" Eulerian averages UE , computed from grid point velocities inside 1 o \Theta 1 o bins for approximately 2 years.
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