We have analyzed the correlation between measurements by three different satellite sensors (SCIAMACHY, MODIS, and CERES) on two independent space platforms (Envisat and Terra). Though the instantaneous measurements from the two satellites are not collocated due to orbit offset, the monthly mean broadband and narrowband reflectances and their anomalies from the three instruments are highly correlated when averaged over large latitude regions. The mean reflectance from MODIS in each of those large domains is nearly the same as that derived from SCIAMACHY spectrum convolved with the filter function of the corresponding MODIS channel, with all correlation coefficients higher than 0.93. The interannual variability of monthly mean reflectance is also correlated with the variations of mean cloud and surface properties in large climate zones. The reflectance variation is correlated with the cloud fraction in low and middle latitude regions with correlation coefficients higher than 0.76 and with the snow and sea ice changes in the polar regions with correlation coefficients higher than 0.6. These correlations indicate that the nadir sampling strategy as proposed for CLARREO is sufficient for climate benchmarking of the reflected solar spectrum and provide the physical foundation for climate fingerprinting. However, the results also show the relatively large differences in trends in reflectance due to different instrument degradations and inconsistent calibrations which will affect the attribution of radiative signals of long-term climate change.