  Observations of Type Ia supernovae used to map the expansion history of the
Universe suffer from systematic uncertainties that need to be propagated into
the estimates of cosmological parameters. We propose an iterative Monte-Carlo
simulation and cosmology fitting technique (SMOCK) to investigate the impact of
sources of error upon fits of the dark energy equation of state. This approach
is especially useful to track the impact of non-Gaussian, correlated effects,
e.g. reddening correction errors, brightness evolution of the supernovae,
K-corrections, gravitational lensing, etc. While the tool is primarily aimed
for studies and optimization of future instruments, we use the ``Gold''
data-set in Riess et al. (2007) to show examples of potential systematic
uncertainties that could exceed the quoted statistical uncertainties.
