机载微波辐射计大气温湿廓线反演性能分析  

Analysis of atmospheric parameter retrievals from airborne microwave sounding instruments

作　　者：谭泉[1,2] 姚志刚 赵增亮 韩志刚 孙学金[2] 

机构地区：[1]北京应用气象研究所,北京100029 [2]解放军理工大学气象海洋学院,南京211101

出　　处：《气象水文海洋仪器》2014年第3期5-11,共7页Meteorological,Hydrological and Marine Instruments

摘　　要：基于RTTOV实现了机载平台的大气微波辐射传输快速计算,给出了机载微波遥感的权重函数;结合ECMWF大气温、湿廓线库建立了用于算法开发的训练库和检验库,并基于神经网络反演算法分析了不同通道组合、观测误差、平台飞行高度等因素对机载平台下微波大气温、湿廓线反演性能的影响。结果表明;神经网络反演算法可以简便、高效地利用多波段的观测信息得到大气温、湿廓线,湿度探测通道可有助于大气温度廓线的反演,且50GHz和118.75GHz附近通道对湿度廓线的反演尤其重要,具有良好的互补性;另外,飞机平台高度的降低能够显著改进飞机以下高度一定范围内的大气温度反演结果。Based on the RTTOV,the fast calculation of the atmospheric microwave radiance transfer isachieved, and the weight function of airborne microwave remote sensing is given. The effect of Channelselection,observation error, the platform height on airborne microwave temperature and humidityprofile retrieval performance is analyzed based on neural network inversion algorithm. The resultsshow that artificial neural networks can easily and efficiently retrieve profiles from multi-bandmicrowave observation information. The humidity detection channels near 50 GHz and 118.75 GHz arenot only important but complementary for humidity profile retrievals. In particular, with the reductionof aircraft cruising altitude, temperature retrieval error can be reduced within a certain height belowthe aircraft.

关 键 词：温度 湿度 机载 微波 

分 类 号：P412.24[天文地球—大气科学及气象学]