Wind turbines located in cold climates and in elevated terrain are often at risk of ice accretion when supercooled water droplets within clouds interact with the surface of the turbine blade structure. The accurate forecast of generation losses during these icing events is necessary for the operation of wind farms. In order to accurately predict wind generation losses, meteorological input is required from numerical weather prediction (NWP) models that are in turn required to resolve the complex interaction between the surface and the atmosphere—more specifically the wind, temperature and clouds within the atmospheric boundary layer. Surface-boundary layer interactions are sub-grid scale processes within operational NWP models and must be parameterized. To further add to the complexity wind farms are often located within regions of heterogeneous land use, which can hinder accurate representation of the surface in the NWP model. The impact of the land-use on the low-level clouds can potentially be important for the forecasting of icing and related power generation losses. This study will explore the sensitivity of land use on the forecast of low-level supercooled clouds using a one column model called Modèle Unifié, Simple Colonne (MUSC), which was developed in a collaboration between Météo-France and the Aladin and Hirlam consortiums. MUSC is a one-dimensional version of the HARMONIE-AROME operational mesoscale model, which utilizes the SURFEX surface scheme. First results will be shown and validated against observational data from the Swedish Hornamossen meteorological observation site.