The cloud albedo in the marine subtropical stratocumulus regions plays a key role in regulating the regional energy budget. Based on 12 years of monthly data from multiple satellite datasets, the long-term, monthly and seasonal cycle of averaged cloud albedo in five stratocumulus regions were investigated to intercompare the atmosphere-only simulations between phases 5 and 6 of the Coupled Model Intercomparison Project (AMIP5 and AMIP6). Statistical results showed that the long-term regressed cloud albedos were underestimated in most AMIP6 models compared with the satellite-driven cloud albedos, and the AMIP6 models produced a similar spread as AMIP5 over all regions. The monthly averaged values and seasonal cycle of cloud albedo of AMIP6 ensemble mean showed a better correlation with the satellite-driven observations than that of the AMIP5 ensemble mean. However, the AMIP6 model still failed to reproduce the values and amplitude in some regions. By employing the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) data, this study estimated the relative contributions of different aerosols and meteorological factors on the long-term variation of marine stratocumulus cloud albedo under different cloud liquid water path (LWP) conditions. The multiple regression models can explain â¼ 65 % of the changes in the cloud albedo. Under the monthly mean LWP [less than or equal to] 65 g m.sup.-2, dust and black carbon dominantly contributed to the changes in the cloud albedo, while dust and sulfur dioxide aerosol contributed the most under the condition of 65 g m.sup.-2 LWP [less than or equal to] 120 g m.sup.-2 . These results suggest that the parameterization of cloud-aerosol interactions is crucial for accurately simulating the cloud albedo in climate models.