This study isolates and quantifies the two factors controlling Northern Hemisphere springtime snow albedo feedback in transient climate change simulations using 17 climate models from the IPCC Fourth Assessment Report. The first factor is the dependence of planetary albedo on surface albedo, representing the atmosphere's attenuation effect on surface albedo anomalies. An analytical model was developed to calculate this dependence, showing that surface albedo anomalies are attenuated by about half in Northern Hemisphere land areas. The intermodel standard deviation in this dependence is small, less than 10% of the mean, and simulations agree with satellite data within about 10%. The second factor is the change in surface albedo due to anthropogenic temperature changes, which exhibits more intermodel variability. The standard deviation is about one-third of the mean, with the largest value being three times larger than the smallest. This factor is the main source of divergence in snow albedo feedback simulations. The study concludes that differences in cloud fields do not significantly affect the first factor, and that the main source of divergence in simulations is due to differing parameterizations of surface processes. The analytical model accurately captures planetary albedo variations and shows good agreement with satellite data. The mean value of the first factor is about 0.5, indicating that snow-induced planetary albedo anomalies are about half the albedo signature at the surface. The second factor, related to surface processes, is the main source of divergence in simulations of snow albedo feedback.This study isolates and quantifies the two factors controlling Northern Hemisphere springtime snow albedo feedback in transient climate change simulations using 17 climate models from the IPCC Fourth Assessment Report. The first factor is the dependence of planetary albedo on surface albedo, representing the atmosphere's attenuation effect on surface albedo anomalies. An analytical model was developed to calculate this dependence, showing that surface albedo anomalies are attenuated by about half in Northern Hemisphere land areas. The intermodel standard deviation in this dependence is small, less than 10% of the mean, and simulations agree with satellite data within about 10%. The second factor is the change in surface albedo due to anthropogenic temperature changes, which exhibits more intermodel variability. The standard deviation is about one-third of the mean, with the largest value being three times larger than the smallest. This factor is the main source of divergence in snow albedo feedback simulations. The study concludes that differences in cloud fields do not significantly affect the first factor, and that the main source of divergence in simulations is due to differing parameterizations of surface processes. The analytical model accurately captures planetary albedo variations and shows good agreement with satellite data. The mean value of the first factor is about 0.5, indicating that snow-induced planetary albedo anomalies are about half the albedo signature at the surface. The second factor, related to surface processes, is the main source of divergence in simulations of snow albedo feedback.