This paper investigates the factors controlling the Northern Hemisphere (NH) springtime snow albedo feedback in transient climate change scenarios using 17 climate models from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. The authors focus on two key factors: the dependence of planetary albedo on surface albedo and the change in surface albedo due to anthropogenically induced temperature changes. The first factor, which represents the atmosphere's attenuation effect on surface albedo anomalies, is found to be a significant source of divergence in simulations due to large differences in cloud fields. An analytical model is developed to calculate this dependence, which is validated against simulations and satellite-based data from the International Satellite Cloud Climatology Project (ISCCP). The model shows that surface albedo anomalies are attenuated by approximately half in NH land areas as they are transformed into planetary albedo anomalies, with intermodel standard deviation being less than 10% of the mean. The second factor, related to surface processes, exhibits more intermodel variability, with a standard deviation of about one-third of the mean. This factor is identified as the main source of divergence in simulations of snow albedo feedback. The study concludes that focusing on differing parameterizations of snow processes rather than intermodel variations in the atmospheric attenuation effect can help reduce this divergence.This paper investigates the factors controlling the Northern Hemisphere (NH) springtime snow albedo feedback in transient climate change scenarios using 17 climate models from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. The authors focus on two key factors: the dependence of planetary albedo on surface albedo and the change in surface albedo due to anthropogenically induced temperature changes. The first factor, which represents the atmosphere's attenuation effect on surface albedo anomalies, is found to be a significant source of divergence in simulations due to large differences in cloud fields. An analytical model is developed to calculate this dependence, which is validated against simulations and satellite-based data from the International Satellite Cloud Climatology Project (ISCCP). The model shows that surface albedo anomalies are attenuated by approximately half in NH land areas as they are transformed into planetary albedo anomalies, with intermodel standard deviation being less than 10% of the mean. The second factor, related to surface processes, exhibits more intermodel variability, with a standard deviation of about one-third of the mean. This factor is identified as the main source of divergence in simulations of snow albedo feedback. The study concludes that focusing on differing parameterizations of snow processes rather than intermodel variations in the atmospheric attenuation effect can help reduce this divergence.