  We present an updated version of GRASS (the GRanulation And Spectrum
Simulator, Palumbo et al. 2022) which now uses an expanded library of 22 solar
lines to empirically model time-resolved spectral variations arising from solar
granulation. We show that our synthesis model accurately reproduces
disk-integrated solar line profiles and bisectors, and we quantify the
intrinsic granulation-driven radial-velocity (RV) variability for each of the
22 lines studied. We show that summary statistics of bisector shape (e.g.,
bisector inverse slope) are strongly correlated with the measured anomalous,
variability-driven RV at high pixel signal-to-noise ratio (SNR) and spectral
resolution. Further, the strength of the correlations vary both line by line
and with the summary statistic used. These correlations disappear for
individual lines at the typical spectral resolutions and SNRs achieved by
current EPRV spectrographs; so we use simulations from GRASS to demonstrate
that they can, in principle, be recovered by selectively binning lines that are
similarly affected by granulation. In the best-case scenario (high SNR and
large number of binned lines), we find that a $\lesssim$30$\%$ reduction in the
granulation-induced root mean square (RMS) RV can be achieved, but that the
achievable reduction in variability is most strongly limited by the spectral
resolution of the observing instrument. Based on our simulations, we predict
that existing ultra-high-resolution spectrographs, namely ESPRESSO and PEPSI,
should be able to resolve convective variability in other, bright stars.
