Clouds cover around two thirds of the Earth’s surface. Most of them are thick enough to influence the radiative budget of our planet: they increase the top of atmosphere (TOA) exitance and they alter the bottom of atmosphere (BOA) direct and diffuse irradiance. However, most radiative transfer models dedicated to Earth surfaces, such as DART (Discrete Anisotropic Radiative Transfer), simulate only cloudless atmospheres. We recently introduced clouds in DART in order to improve the modelling of weather for remote sensing simulations. In this implementation, clouds were characterized with user specified optical properties and vertical distribution. They were modelled as layered one-dimensional medium that coexists with gases and aerosols. The atmospheric radiative transfer modelling relies on the discrete ordinate method already in DART. In addition, an iterative inversion procedure was designed to test this improvement with field measurements during two cloudy days at Lamasquère meteorological station (France). Specifically, it derives time-series of atmosphere parameters from time-series of BOA solar irradiance measurements. These inversed atmospheric parameters were used to simulate total and diffuse BOA irradiance in PAR (Photosynthetically Active Radiation) domain. The comparison of time-series of measured and DART simulated PAR irradiance lead to very encouraging results (mean relative error ∼8% for total irradiance and ∼20% for diffuse irradiance). It stresses the potential of DART to accurately simulate irradiance in cloudy days.