  Owing to recent advances in radial-velocity instrumentation and observation
techniques, the detection of Earth-mass planets around Sun-like stars may soon
be primarily limited by intrinsic stellar variability. Several processes
contribute to this variability, including starspots, pulsations, and
granulation. Although many previous studies have focused on techniques to
mitigate signals from pulsations and other types of magnetic activity,
granulation noise has to date only been partially addressed by
empirically-motivated observation strategies and magnetohydrodynamic
simulations. To address this deficit, we present the GRanulation And Spectrum
Simulator ($\texttt{GRASS}$), a new tool designed to create time-series
synthetic spectra with granulation-driven variability from spatially- and
temporally-resolved observations of solar absorption lines. In this work, we
present $\texttt{GRASS}$, detail its methodology, and validate its model
against disk-integrated solar observations. As a first-of-its-kind empirical
model for spectral variability due to granulation in a star with perfectly
known center-of-mass radial-velocity behavior, $\texttt{GRASS}$ is an important
tool for testing new methods of disentangling granular line-shape changes from
true Doppler shifts.
