As many researchers have already pointed out, clouds are crucial in climate formation and variability studies. In particular, the cloud optical properties such as the optical depth and effective particle radius are important for calculating earth radiation budget. Effect of cloud modification or cloud-aerosol interaction is the most uncertain among cloud-relevant climatic phenomena as IPCC reports indicate, and GCM modelers also suffer from its physical treatment. It has been one of the hottest topics in our recent research community. The final goals of this work are to 1) detect the long-term (from early 80's to present) variability of the cloud properties in East Asia, 2) estimate its magnitude, and 3) have a comprehensive understanding on cloud-related processes, together with aerosol emission and precipitation. We focus the location and period from a reason that China had undergone substantial political changes since 1979, and then subsequent social and economical effects have drastically increased in industrial production and the number of car and so on. This period is also concurrent with availability of satellite data which are mainly used for derivation of cloud properties. We retrieve the cloud optical depth, effective particle radius and cloud top temperature (height) applying Kawamoto et al. (2001) algorithm to AVHRR (Advanced Very High Resolution Radiometer) data. These cloud products will be compared with emission inventory such as SO2 and aerosol optical data derived from ground measurements to investigate their geographical correspondence. Preliminary results of comparison between cloud properties and SO2 emission, however, support Twomey effect, indicating larger optical depth, smaller particle size and more cloud droplet number as SO2 emission increases. Although satellite data are very useful for long-term climate research, we need to be careful to some problems such as sensor degradation, discontinuity of platform and orbital shift. They can easily bring artifacts to the retrieved time-series, so substantial effort should be addressed to reduce the artifact. It is also quite interesting to see the relation of cloud properties with precipitation amount and pattern. This kind of work is important for validation of GCM output, and provides precious information to parameterizations about cloud phenomena.