Here we assess established algorithms and a newly developed scheme for the estimation of downward long-wave radiation flux at the surface (DLR), i.e., the irradiance reaching the surface within 4 and 100 μm. These different methods correspond to bulk parameterization schemes, which merge the signature of clouds on Meteosat second-generation (MSG) data with information on atmosphere water content and near-surface air temperature available from numerical weather prediction (NWP) fields. The new formulation consists of a generalization of a method first developed for clear sky cases and now fine-tuned for a wider range of atmospheric conditions. The performance of this and three other parameterization schemes is compared with independent ground observations. Such a validation exercise is extended also to European Centre for Medium-Range Weather Forecast (ECMWF) flux forecasts, since the ECMWF model is the main source of information on air temperature and water vapor content, and to surface fluxes obtained from the Clouds and the Earth's Radiant Energy System (CERES). It is shown that the new parameterization scheme performs well when compared to other methods, with root mean square errors within 20 Wm−2. The overall good matching between parameterized values and in situ data suggests a good performance of a relatively simple bulk scheme and also of the use of MSG-based cloud identification.