In this paper

the GMS-5 infrared cloud imagery together with surface temperature data of 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 on the base of atmospheric probing principle

then some parameterization estimate results have been obtained under different analysis field from 3×3 to 15×15 pixels. The result shows:1 there exists obvious correlation between the probability of rain and parameterization estimate such as average brightness temperature（Tb）

brightness temperature variance（f）

equivalent cloudage（CN）

brightness temperature area index（A1—the first

A5—the fifth grade

A6—the sixth grade）; 2 The rainfall intensity increase

with Tb and f and CN

and decrease with Tb and A1. Finally

the prediction empirical formula of rainfall intensity has been established by means of optimized subclass regression under different analysis field. The statistical result shows that the average precision of rainfall intensity is over 80% using infrared cloud imagery parameters and the size of analysis field has slight effect on it.