Weather Satellite data has great potential for Precipitation forecast which plays an important role in flood disaster monitoring. In this paper, the GMS-5 infrared cloud imagery combined with surface temperature data for two years in Binjiang reaches of Guangdong province in China is used to study the relationship between infrared cloud imagery and surface rainfall rates. First, parameterization estimate of infrared cloud imagery is made one the base of atmospheric probing principle, then some parameterization estimate result have been obtained under different analysis field from 3×3 to 15×15 pixels. The result shows:1 there exist obvious correlation between the probability of rain and parameterization estimate such as average brightness temperature(Tb), brightness temperature variance(fc), equivalent cloudage(CN),brightness temperature area index(A1--the first A5--the fifth grade, A6-the sixth grade );2 The rainfall intensity increase with Tb and f and CN, and that it decrease with Tb and A1.Finally,the prediction empirical formula of rainfall intensity has been established by means of optimized subclass regression under different analysis field. The following formula is made under analysis field of 11×11 pixels. The statistical result shows that the average precision of rainfall intensity is about 80% using infrared cloud imagery parameters and the size of analysis field has slight effect on it. If the rainfall intensity reached the storm standard, the flood alarm would be sent out.