The movement of clouds is qualitative analyzed by forecasters with satellite images currently

which is

however

lack of objectivity and quantitativity.In this paper

based on the stationary satellite infrared（IR） channel（10.3—11.3 μm） images of FY-2C and FY-2D with the time resolution of 15 minutes

brightness temperature（BT） and area threshold are selected to identify the severe convective cloud（SCC）.We then use the SCC matching algorithm of maximum correlation to track the shorttime automatic prediction of SCC systematically.The experiment results show that the tracking method proposed in this work has higher matching accuracy and efficiency compared with the traditional cross-correlation approach.The cloud center of gravity（CG） extrapolation is markedly superior to the minimum temperature

and the mean temperature

area and roundness all have better indications to the cloud split and merge.Tested by contingency table

the automatic identification and tracking technology has high prediction accuracy and timeliness.In addition

the research of this paper provides a scientific basis for the objective and quantitative application of satellite images to SCC short-time prediction in operation.