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The rapid increase of the globally averaged near-surface air temperature, and the retreat of sea ice represent alarming signals of rapid changes of the Arctic climate system. Climate models systematically underestimate the observed sea ice decrease. Due to lacking crucial observational data (e.g., surface albedo), it is challenging to understand the processes and effects of the changes and to realistically implement them into projections of the Arctic climate system. Using the helicopter-borne probe HELiPOD during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) in summer 2020, simultaneous observations of surface reflection properties and meteorological parameters were collected. This contribution analyzes images of the surface obtained simultaneously by a fisheye camera and broadband solar radiation by upward and downward looking pyranometers. Based on the camera images, the observed surfaces were classified by an RGB approach into white ice/snow, bright melt ponds, dark melt ponds and open water. The classification is used to evaluate the current surface albedo scheme (SAS) of the High-Resolution High Area-North Atlantic/Arctic Ocean-Sea Ice Model (HIRHAM-NAOSIM). The results show an underestimation of the natural variability and an overestimation of the surface albedo, which can be mainly attributed to the insufficient parameterization of the surface type fractions. [ABSTRACT FROM AUTHOR]