  Flows on the solar surface are linked to solar activity, and LCT is one of
the standard techniques for capturing the dynamics of these processes by
cross-correlating solar images. However, the link between contrast variations
in successive images to the underlying plasma motions has to be quantitatively
confirmed. Radiation hydrodynamics simulations of solar granulation
(e.g.,CO5BOLD) provide access to both the wavelength-integrated, emergent
continuum intensity and the 3D velocity field at various heights in the solar
atmosphere. Thus, applying LCT to continuum images yields horizontal proper
motions, which are then compared to the velocity field of the simulated
(non-magnetic) granulation. In this study, we evaluate the performance of an
LCT algorithm previously developed for bulk-processing Hinode G-band images,
establish it as a quantitative tool for measuring horizontal proper motions,
and clearly work out the limitations of LCT or similar techniques designed to
track optical flows. Horizontal flow maps and frequency distributions of the
flow speed were computed for a variety of LCT input parameters including the
spatial resolution, the width of the sampling window, the time cadence of
successive images, and the averaging time used to determine persistent flow
properties. Smoothed velocity fields from the hydrodynamics simulation at three
atmospheric layers (log tau=-1,0,and +1) served as a point of reference for the
LCT results. LCT recovers many of the granulation properties, e.g.,the shape of
the flow speed distributions, the relationship between mean flow speed and
averaging time, and also--with significant smoothing of the simulated velocity
field--morphological features of the flow and divergence maps. However, the
horizontal proper motions are grossly underestimated by as much as a factor of
three. The LCT flows match best the flows deeper in the atmosphere at log
tau=+1.
