One major challenge in representing the state of the atmosphere through weather forecast models, is the parametrization of sub-grid clouds. At every vertical column of grid cells within a weather forecast model, the fractional cloud cover is assumed to overlap according to a prescribed Cloud Overlap Assumption (COA). Since the total cloud cover is used in radiation schemes, the choice of COA affects e.g. radiative fluxes. High-quality weather forecasts is important for many aspects of the society, thus, the analysis of cloud parametrizations is significant. In this study, COAs for the HIRLAM ALADIN Research on mesoscale Modelling for NWP In Euromed (HARMONIE) - Application of Research to Operations at Mesoscale (AROME) model were investigated for two time-periods. Moreover, validation methods of cloud cover for HARMONIE-AROME were analyzed due to uncertainties in cloud observations. Both satellite data derived from geostationary Meteosat Second Generation (MSG) satellite and synoptic ground based observations were used to validate cloud cover in this project. It was found that HARMONIE-AROME underestimates the cloud cover during summer. Therefore, the random (RAN) COA is the preferred COA to use during time periods of mainly convective cloud processes. During the tested winter period, which is assumed to have most clouds of the stratiform type, the results regarding optimal COA were not certain. However, it was concluded that HARMONIE-AROME overestimates the cloud cover during winter, for in which case the maximum-random (MRN) COA is recommended to use. The comparative analysis of cloud cover as obtained from the COAs against observed cloud cover, was shown sensitive to the methods used to the observational data. Using a model grid of 25 km instead of 2.5 km when comparing synoptic observations to modelled cloud cover, the errors were reduced. When using binary satellite data, it was concluded that a 5x5 smoothing algorithm was the most appropriate to use since this averaging of several pixels are sufficient to represent sub-grid clouds.