  We develop a novel data-driven method for generating synthetic optical
observations of galaxy clusters. In cluster weak lensing, the interplay between
analysis choices and systematic effects related to source galaxy selection,
shape measurement and photometric redshift estimation can be best characterized
in end-to-end tests going from mock observations to recovered cluster masses.
To create such test scenarios, we measure and model the photometric properties
of galaxy clusters and their sky environments from the Dark Energy Survey Year
3 (DES Y3) data in two bins of cluster richness $\lambda\in[30;\,45)$,
$\lambda\in[45;\,60)$ and three bins in cluster redshift ($z\in[0.3;\,0.35)$,
$z\in[0.45;\,0.5)$ and $z\in[0.6;\,0.65)$. Using deep-field imaging data we
extrapolate galaxy populations beyond the limiting magnitude of DES Y3 and
calculate the properties of cluster member galaxies via statistical background
subtraction. We construct mock galaxy clusters as random draws from a
distribution function, and render mock clusters and line-of-sight catalogs into
synthetic images in the same format as actual survey observations. Synthetic
galaxy clusters are generated from real observational data, and thus are
independent from the assumptions inherent to cosmological simulations. The
recipe can be straightforwardly modified to incorporate extra information, and
correct for survey incompleteness. New realizations of synthetic clusters can
be created at minimal cost, which will allow future analyses to generate the
large number of images needed to characterize systematic uncertainties in
cluster mass measurements.
