Estimation of aerosol direct radiative forcing (DRF) from satellite measurements is challenging because current satellite sensors do not have the capability of discriminating between anthropogenic and natural aerosols. We combine 3-hourly cloud properties from satellite retrievals with two aerosol data sets to calculate the all-sky aerosol direct radiative effect (DRE), which is the mean radiative perturbation due to the presence of both natural and anthropogenic aerosols. The first aerosol data set is based upon Moderate Resolution Imaging Spectroradiometer (MODIS) and Model for Atmospheric Transport and Chemistry (MATCH) assimilation model and is largely constrained by MODIS aerosol optical depth, but it does not distinguish between anthropogenic and natural aerosols. The other aerosol data set is based upon the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which does not assimilate aerosol observations but predicts the anthropogenic and natural components of aerosols. Thus, we can calculate the aerosol DRF using GOCART classifications of anthropogenic and natural aerosols and the ratio of DRF to DRE. We then apply this ratio to DRE calculated using MODIS/MATCH aerosols to partition it into DRF (MODIS/MATCH DRF) by assuming that the anthropogenic fractions from GOCART are representative. The global (60 N~60 S) mean all-sky MODIS/MATCH DRF is -0.51 Wm-2 at the top of the atmosphere (TOA), 2.51 Wm-2 within the atmosphere, and -3.02 Wm-2 at the surface. The GOCART all-sky DRF is -0.17 Wm-2 at the TOA, 2.02 Wm-2 within the atmosphere, and -2.19 Wm-2 at the surface. The differences between MODIS/MATCH DRF and GOCART DRF are solely due to the differences in aerosol properties, since both computations use the same cloud properties and surface albedo and the same proportion of anthropogenic contributions to aerosol DRE. Aerosol optical depths simulated by the GOCART model are smaller than those in MODIS/MATCH, and aerosols in the GOCART model are more absorbing than those in MODIS/MATCH. Large difference in all-sky TOA DRF from these two aerosol data sets highlights the complexity in determining the all-sky DRF, since the presence of clouds amplifies the sensitivities of DRF to aerosol singlescattering albedo and aerosol vertical distribution.