This presentation highlights IRIS, a Python tool for the simulation of space-based greenhouse gas (GHG) observation missions, currently in development. IRIS simulates radiative transfer from solar irradiance to top-of-atmosphere radiances at the entrance of a spaceborne instrument, accounting for the passage through Earth's atmosphere and reflection from the terrestrial surface. The simulator will incorporate modules for instrument simulation (applying spectral response functions, noise, calibration biases) and greenhouse gas retrieval using a Levenberg-Marquardt algorithm.

The tool is designed to run a significant number of simulations addressing various geophysical, observational, and instrumental configurations. It can currently simulate low spectral resolution (2.5 nm) radiances and transmittances using the Py6S Python wrapper for the 6SV radiative transfer code. These first-order simulations will provide orders of magnitude of radiances at the sensor level, and enable acquisition conditions to be fine-tuned. Subsequently, another radiative transfer tool will be integrated into IRIS to obtain highly resolved TOA radiance spectra. These spectra will be used to accurately simulate the instrument and assess the mission's capacity to retrieve GHGs. The foreseen code for this task is SCIATRAN.

The impact of different conditions on radiances and transmittances have been obtained for the preparation of the Uvsq-Sat NG mission. IRIS represents a crucial tool for the development of space-based GHG observation missions.