基于FY-2C红外资料进行夜间云检测的方法研究

A Method of Cloud Detection at Nighttime Using FY-2C Infrared Channel Data

应用2007年4月30日20时至5月1日03时的FY-2C红外亮温资料、地面云观测资料以及地理海拔高度资料,详细分析了无云条件下红外亮温与地理海拔高度之间的关系特征。通过建立夜间无云条件下红外亮温与地理海拔高度之间对应关系的标准数据库,以此为判据实现了有云区和无云区的分离,云检测个例结果表明正确率可达88%;将无云区误判为有云区的百分比为4%,同时将有云区误判为晴空区的百分比是8%。在云区的云检测正确率为82%;在无云区的云检测正确率达到92%。在业务化应用和适用性分析中,以5月1日00时资料建立的判据,分别对5月2日至5日00时整个区域进行云检测试验,分析结果表明其总体准确率与5月1日00时的基本接近但稍高,达到92%。在云区的判识正确率提高到93%,从而导致总体准确率稍微提高;而在无云区的判识效果与5月1日00时的一致为92%。

Based on the surface topographic altitude data,FY-2C infrared channel data and cloud cover data from observation stations during 30 April—01 May 2007 from 2000 to 0300（UTC）,an analysis of the relation between the topographic altitude and the clear IR radiance is performed.It is found that the IR brightness temperature of surface is influenced by the change of surface topographic altitudes at nighttime in clear areas.The IR brightness temperature in some clear areas at high altitude is lower than（or equal to） that in other cloudy areas at low altitude.This results in difficulty to process cloud detection using infrared channel data.Therefore,the standard database of clear surface IR brightness temperature at different topographic altitudes is established and used to separate satellite infrared observations into＂clear＂and＂cloudy＂categories as a method at nighttime.A case selected randomly shows that 88 percent of satellite observations can be correctly separated for an infrared imagery at nighttime.There are 4 percent of＂clear＂observations to be incorrectly separated into＂cloudy＂ones.In addition,8 percent of＂cloudy＂observations are incorrectly separated into＂clear＂category.By the method 92 percent of satellite observations in clear areas can be correctly categorized,but 82 percent in cloudy areas.In order to analyze the operational use of the method the satellite infrared observations at 0000 UTC during 2—5 May 2007 are separated into＂clear＂and＂cloudy＂categories based on the standard database from the datasets at 0000 UTC 1 May 2007.The 92 percent of total satellite observations can be correctly separated,and the accuracy is close to, but better than that of cloud detection at 0000 UTC 1 May.The 93 percent of satellite observations in clear areas can be correctly categorized,which results in the better total accuracy,also 92 percent in cloudy areas.