| Summary: | The Greenland Ice Sheet has been in a state of negative mass balance for the past several decades and is currently responsible for a substantial proportion of global sea-level rise. Accurate projections of ice sheet mass loss are therefore imperative, and a number of regional climate models (RCMs) have been developed for this purpose. However, a recent intercomparison (GrSMBMIP) of surface mass balance (SMB) models demonstrated substantial discrepancies between their individual projections. One likely explanation for model spread is inaccurate simulation of albedo, which determines the amount of shortwave radiation that is absorbed by the ice sheet surface. Here, we force a state-of-the-art surface energy balance model (IceModel v1.0) with four albedo products to investigate the sensitivity of meltwater production to different albedo parameterizations for the 2009-2022 period. The four albedo products include one product from satellite observations (MODIS MCD43A3), which we treat as “ground-truth”, one atmospheric reanalysis (MERRA-2), and two RCMs (MAR v3.12.1 and RACMO2.3p2). We find that, for fifteen of automated weather stations located at the margins of the ice sheet, MAR and MERRA-2, on average, overestimate observed (MODIS) glacier ice albedo by +0.11 and +0.13, respectively, while RACMO underestimates it by -0.07. These biases mean that IceModel underestimates melt -36.3% and -27.1% when forced by albedo derived from MAR and MERRA-2, respectively. In contrast, IceModel overestimates melt by +5.5% when forced by albedo derived from RACMO. We also identify several compensating effects in our analysis. We also highlight the presence of counteractive errors of albedo representations in all models that result in diminished uncertainty. Specifically, RACMO tends to overestimate snow albedo, while generally underestimating glacier ice albedo, which results in an estimate that appears to be more accurate relative to observations. Ultimately, based on the partitioned information that we outline further in this ...
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