  We present FORECAST, a new flexible and adaptable software package that
performs forward modeling of the output of any cosmological hydrodynamical
simulations to create a wide range of realistic synthetic astronomical images.
With customizable options for filters, field of view size and survey
parameters, it allows users to tailor the synthetic images to their specific
requirements. FORECAST constructs light-cone exploiting the output snapshots of
a simulation and computes the observed flux of each simulated stellar element,
modeled as a Single Stellar Population, in any chosen set of pass-band filters,
including k-correction, IGM absorption and dust attenuation. As a first
application, we emulated the GOODS-South field as observed for the CANDELS
survey exploiting the IllustrisTNG simulation. We produce images of 200 sq.
arcmin., in 13 bands (eight Hubble Space Telescope optical and near-infrared
bands from ACS B435 to WFC3 H160, the VLT HAWK-I Ks band, and the four IRAC
filters from Spitzer), with depths consistent with the real data. We analysed
the images with the same processing pipeline adopted for real data in CANDELS
and ASTRODEEP publications, and we compared the results against both the input
data used to create the images, and real data, generally finding good agreement
with both, with some interesting exceptions which we discuss. As part of this
work, we release the FORECAST code and two datasets: the CANDELS dataset
analyzed in this study, and 10 JWST CEERS survey-like images (8 NIRCam and 2
MIRI) in a field of view of 200 sq. arcmin. between z=0-20. FORECAST is a
flexible tool: it creates images that can then be processed and analysed using
standard photometric algorithms, allowing for a consistent comparison among
observations and models, and for a direct estimation of the biases introduced
by such techniques.
