Abstract: The Particle Filter (PF) cloud retrieval method developed in the framework of GSI (Gridpoint Statistical Interpolation analysis system) is able to directly utilize the _Infrared radiances to retrieve cloud masks and cloud profiles. Cloud retrieval experiments with GOES (Geostationary Operational Environmental Satellites)-Imager radiance are conducted with the PF and the Multivariate and Minimum Residual (MMR) methods respectively for comparison. The retrieved cloud properties from both methods show a good agreement with the cloud products from GOES. MMR retrieves cloud fractions on each individual model vertical levels by minimizing a cost function, while PF is an effective algorithm to treat those cloud fractions as different particles to gain recursive estimations of cloud distributions. To improve the PF method in terms of cloud retrieval application, this study perturbs the particles to better estimate cloud distributions. The advanced PF (with roughly 250 samples) is appropriate to ameliorate the problem of filter divergence caused by limited particles with better cloud retrievals efficiently.