应用SVM技术模拟前向辐射传输模式  

Simulating radiative transfer forward model using support vector machine technique

作　　者：谭永强[1] 费建芳[1] 

机构地区：[1]解放军理工大学气象学院,江苏南京211101

出　　处：《遥感学报》2009年第2期257-262,共6页NATIONAL REMOTE SENSING BULLETIN

基　　金：中国科学院大气物理研究所大气科学和地球流体力学国家重点实验室开放课题2709;中国气象局上海台风研究所开放课题(编号:2006STB02)

摘　　要：提出了一种利用支持向量机(SVM)模拟前向辐射传输模式的方法。利用欧洲中期天气预报中心(ECMWF)的RTTOV_8_7前向辐射传输模式和60L-SD廓线集生成了AMSU-A模拟亮温资料,用模拟亮温和相应的廓线集资料组成训练样本和检验样本,采用SVM方法进行训练。对检验样本的模拟显示,SVM可以用于描写前向辐射传输模式中的非线性映射关系,较好地由大气廓线集资料模拟出与其相关的AMSU-A仪器5—14通道亮温,其中通道6—14的均方根误差在0.1K以内,平均误差算术平均值在0.01K以内。通过多元线性回归方法对温度廓线进行反演试验,发现用SVM模拟的亮温可以用于温度廓线反演,其反演精度可以达到甚至高于RTTOV_8_7计算的亮温。Based on Support Vector Machine（SVM）, a technique simulating radiative transfer forward model is presented. Using European Centre for Medium-Range Weather Forecasts （ECMWF） RTTOV _8 _7 radiative transfer forward model and 60L_SD profile database, we simulate the brightness temperature received in AMSU-A instrument. Combine this brightness temperature datasets and correspondence profile datasets as training and validation database. After training the SVM network, the simulating technique is validated. The results show that SVM network describes the nonlinear projection relationship between input space and output space very well, and the simulated brightness temperature of channel 5--14 is precise. The RMS error of channel 6--14 is less than 0.1K and the mean standard deviation is less than 0.01K. In order to find whether SVM simulated brightness temperature is appropriate for temperature retrieval, muti-regression retrieval method is used to retrieve temperature profile. Experiment result shows that the SVM simulate brightness temperature is appropriate for the purpose, and the retrieval precision is not only equally but also a little more precise than the RTTOV_ 8_ 7 simulated brightness temperature.

关 键 词：SVM 前向辐射传输模式 RTTOV 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP79[自动化与计算机技术—控制科学与工程]