  We employ different shapes of apodizing windows in the local correlation
tracking (LCT) routine to retrieve horizontal velocities using numerical
simulations of convection. LCT was applied on a time sequence of temperature
maps generated by the Nirvana code with four different apodizing windows,
namely--Gaussian, Lorentzian, trapezoidal and triangular, with varying widths.
In terms of correlations (between the LCT-retrieved and simulated flow field),
the triangular and the trapezoidal perform the best and worst, respectively. On
segregating the intrinsic velocities in the simulations on the basis of their
magnitudes, we find that for all windows, a significantly higher correlation is
obtained for the intermediate and high-velocity bins and only modest or weak
values in the low-velocity bins. The differences between the LCT-retrieved and
simulated flow fields were determined spatially which show large residuals at
or close to the boundary of granules. The extent to which the horizontal flow
vectors retrieved by LCT compare with the simulated values, depends entirely on
the width of the central peak of the apodizing window for a given $\sigma$.
Even though LCT suffers from a lack of spatial content as seen in simulations,
its simplicity and speed could serve as a viable first-order tool to probe
horizontal flows--one that is ideal for large data sets.
