Flows on the solar surface are linked to solar activity, and LCT is one ofthe standard techniques for capturing the dynamics of these processes bycross-correlating solar images. However, the link between contrast variationsin successive images to the underlying plasma motions has to be quantitativelyconfirmed. Radiation hydrodynamics simulations of solar granulation(e.g.,CO5BOLD) provide access to both the wavelength-integrated, emergentcontinuum intensity and the 3D velocity field at various heights in the solaratmosphere. Thus, applying LCT to continuum images yields horizontal propermotions, which are then compared to the velocity field of the simulated(non-magnetic) granulation. In this study, we evaluate the performance of anLCT 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 totrack optical flows. Horizontal flow maps and frequency distributions of theflow speed were computed for a variety of LCT input parameters including thespatial resolution, the width of the sampling window, the time cadence ofsuccessive images, and the averaging time used to determine persistent flowproperties. Smoothed velocity fields from the hydrodynamics simulation at threeatmospheric layers (log tau=-1,0,and +1) served as a point of reference for theLCT results. LCT recovers many of the granulation properties, e.g.,the shape ofthe flow speed distributions, the relationship between mean flow speed andaveraging time, and also--with significant smoothing of the simulated velocityfield--morphological features of the flow and divergence maps. However, thehorizontal proper motions are grossly underestimated by as much as a factor ofthree. The LCT flows match best the flows deeper in the atmosphere at logtau=+1.
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