摘要
利用中国气象局大气探测试验基地的微波辐射计亮温值、对应的云雷达测得的反射率因子和L波段探空数据,采用BP(back propagation)神经网络作为反演工具,反演得到大气垂直湿度廓线。将天气情况分为晴天、低云、中云和高云四种情况,对比不加入反射率因子的反演湿度廓线,分析两种反演方法在各高度层的均方根误差。对比结果表明,加入反射率因子的反演湿度廓线与探空廓线的相关系数平均值为0.862,均方根误差为14. 9%,而不添加反射率因子的相关系数平均值为0.763,均方根误差为19.2%。
By using the brightness temperature value of the microwave radiometer, the corresponding reflectivity factor of the cloud radar and the L band radiosonde data in the CMA Meteorological Observation Centre, the BP (back propagation) neural network is used as the inversion tool, and the atmospheric humidity profile is retrieved. The weather condition is divided into clear day, low cloud, middle cloud, high cloud as four cases. The inversions of the humidity profiles without reflectivity factor are compared, and the root mean square errors by the two inversion methods in each altitude layer are analyzed. The comparison results show that the correlation coefficient of the inversed humidity profile with the reflectivity factor is 0.862, the root mean square error is 14.9%. On the contrary, the correlation coefficient of the inversed humidity profile without the reflectivity factor is 0.763, and the root mean square error is 19.2%.
作者
丁虹鑫
马舒庆
杨玲
车云飞
DING Hongxin;MA Shuqing;YANG Ling;CHE Yunfei(Chengdu University of Information Technology, Chengdu 610225;CMA Meteorological Observation Centre, Beijing 100081;CMA Key Laboratory of Atmospheric Sounding, Chengdu 610225;Chinese Academy of Meteorological Sciences, Beijing 100081)
出处
《气象》
CSCD
北大核心
2018年第12期1604-1611,共8页
Meteorological Monthly
基金
国家重大科研仪器研制项目(31727901)资助
关键词
微波辐射计
雷达反射率因子
大气湿度廓线
BP神经网络
microwave radiometer
reflectivity factor
humidity profile
BP (back propagation) neural network
