Energy balance based glacier melt models require accurate estimates of incoming longwave radiation but direct measurements are often not available. Multi-year near-surface meteorological data from Storglaciären, Northern Sweden, were used to evaluate commonly used longwave radiation parameterizations in a glacier environment under clear-sky and all-sky conditions. Parameterizations depending solely on air temperature performed worse than those which include water vapor pressure. All models tended to overestimate incoming longwave radiation during periods of low longwave radiation, while incoming longwave was underestimated when radiation was high. Under all-sky conditions root mean square error (RMSE) and mean bias error (MBE) were 17 to 20 W m<sup>&minus;2</sup> and &minus;5 to 1 W m<sup>&minus;2</sup>, respectively. Two attempts were made to circumvent the need of cloud cover data. First cloud fraction was parameterized as a function of the ratio, &tau;, of measured incoming shortwave radiation and calculated top of atmosphere radiation. Second, &tau; was related directly to the cloud factor (i.e. the increase in sky emissivity due to clouds). Despite large scatter between &tau; and both cloud fraction and the cloud factor, resulting calculations of hourly incoming longwave radiation for both approaches were only slightly more variable with RMSE roughly 3 W m<sup>&minus;2</sup> larger compared to using cloud observations as input. This is promising for longwave radiation modeling in areas where shortwave radiation data are available but cloud observations are not