FY-3B红外分光计亮温资料的云检测算法研究  

Cloud Detection Method for Brightness Temperature Data from FY-3B Infrared Atmospheric Sounder

作　　者：王根[1,2] 谢伟[1,3] 陆其峰[4] 张建伟[2] 

机构地区：[1]安徽省气象信息中心,安徽合肥230031 [2]南京信息工程大学数学与统计学院,江苏南京210044 [3]南京大学大气科学系,江苏南京210093 [4]国家卫星气象中心,北京100081

出　　处：《红外》2014年第11期23-27,45,共6页Infrared

基　　金：气象行业专项(GYHY201406028;GYHY201106014;GYHY201206002);国家自然科学基金项目(40705037)

摘　　要：结合风云三号B星(FY-3B)载红外分光计(InfraRed Atmospheric Sounder,IRAS)资料的通道特性,分析了云在不同波段的光谱特性。与通道亮温偏差阈值法不同,利用通道多光谱信息以及基于平滑梯度和通道信噪比的方法对FY-3B/IRAS资料进行云检测方法研究,更有效地识别出了有云视场点。对2013年1月9日00时至1月14日00时共5天的IRAS资料数据进行了偏差订正,然后采用以上方法进行了IRAS资料云检测。结果表明,经过云检测后的通道亮温偏差服从高斯分布,满足后期变分同化IRAS通道亮温的要求。According to the channel characteristics of the data acquired by the Infrared Atmospheric Sounder（IRAS） onboard FY-3B meteorological satellite,the spectral characteristics of cloud in different channels are analyzed.Unlike the threshold method based on channel brightness temperature deviation,the channel multispectral information and the method based on smooth gradient and channel signal-tonoise ratio are used to study the cloud detection of the data from FY-3B/IRAS.The cloud field-of-view is identified effectively.The deviation of the IRAS data from 00 UTC,9 Jan,2013 to 00 UTC 14 Jan,2013 is corrected.Then,the cloud detection is conducted for the IRAS data.The result shows that the channel brightness temperature deviation after cloud detection obeys Gaussian distribution and meets the subsequent variational assimilation requirements of channel brightness for FY-3B/IRAS.

关 键 词：风云三号B星 红外分光计 云检测 平滑梯度法 通道信噪比 

分 类 号：P407.6[天文地球—大气科学及气象学]