Passive satellite cloud property retrievals have been invaluable in gaining an understanding of clouds and their impact on climate. They are also being used to help improve numerical weather prediction model analyses and short-term forecasts, and are used by the aviation community. Retrievals from active sensors on polar orbiting satellites are providing valuable cloud data and structure in the vertical scale along the polar orbiting tracks. The active sensors on the NASA A-Train satellites CloudSat and CALIPSO can be used to derive cloud properties to a higher level of accuracy compared to those derived using passive sensors on GOES and Aqua, which makes a good data source for validating the passive-sensor retrievals. Comparison of GOES and Aqua-MODIS cloud property retrievals ensures that there will be a consistency from the mid to high latitudes as only MODIS retrievals are available above 70N. For this study, the derived cloud properties that are compared include cloud amount, height, optical depth, particle size, and water path for both single layer and multilayer ice-over-liquid clouds.