Observed monthly mean cloud cover from the SHEBA site is found to differ by a substantial amount during winter depending on cloud observing instrument. This makes it difficult for climate modelers to evaluate modeled clouds and improve parameterizations. Many instruments and human observers cannot properly detect the thinnest clouds and count them as clear sky instead, resulting in too low cloud cover. To study the impact from the difficulties in the detection of thin clouds, we compute cloud cover in our model with a filter that removes the thinnest clouds. Optical thickness is used as a proxy to identify thin clouds as we are mainly interested in the impact of clouds on radiation. With the results from a regional climate model simulation of the Arctic, we can reproduce the large variability in wintertime cloud cover between instruments when assuming different cloud detection thresholds. During winter a large fraction of all clouds are optically thin, which causes the large sensitivity to filtering by optical thickness. During summer, most clouds are far above the optical thickness threshold and filtering has no effect. A fair comparison between observed and modeled cloud cover should account for thin clouds that may be present in models but absent in the observational data set. Difficulties with the proper identification of clouds and clear sky also has an effect on cloud radiative forcing. The derived clear-sky longwave flux at the surface can vary by some W m-2 depending on the lower limit for the optical thickness of clouds. This impacts on the observed LW cloud radiative forcing and suggests great care is needed in using satellite-derived cloud radiative forcing for model development.