  End-to-end mission performance simulators (E2ES) are suitable tools to
accelerate satellite mission development from concet to deployment. One core
element of these E2ES is the generation of synthetic scenes that are observed
by the various instruments of an Earth Observation mission. The generation of
these scenes rely on Radiative Transfer Models (RTM) for the simulation of
light interaction with the Earth surface and atmosphere. However, the execution
of advanced RTMs is impractical due to their large computation burden.
Classical interpolation and statistical emulation methods of pre-computed
Look-Up Tables (LUT) are therefore common practice to generate synthetic scenes
in a reasonable time. This work evaluates the accuracy and computation cost of
interpolation and emulation methods to sample the input LUT variable space. The
results on MONDTRAN-based top-of-atmosphere radiance data show that Gaussian
Process emulators produced more accurate output spectra than linear
interpolation at a fraction of its time. It is concluded that emulation can
function as a fast and more accurate alternative to interpolation for LUT
parameter space sampling.
