基于统计与光程分布的二氧化碳反演方法  

Carbon Dioxide Retrieval Method Based on Statistics and Optical Path Distribution

作　　者：段锋华 王先华[1] 叶函函[1] 蒋芸[1,2] 吴浩[1,2] 

机构地区：[1]中国科学院安徽光学精密机械研究所中国科学院通用光学定标与表征技术重点实验室,安徽合肥230031 [2]中国科学技术大学,安徽合肥230026

出　　处：《光学学报》2017年第5期18-24,共7页Acta Optica Sinica

基　　金：国家自然科学基金(41175037);国家自然科学基金青年科学基金(41601393);高分辨对地观测系统重大专项(民用部分)(32-Y20A17-9001-15/17)

摘　　要：为了研究气候变化,需要实现遥感卫星对二氧化碳(CO_2)的高精度测量。气溶胶和透射率较高的薄卷云的散射是影响大气中CO_2反演精度的主要环境因素。结合主成分分析(PCA)的统计方法和光程概率分布的密度函数(PPDF)方法,利用PCA方法得到大气CO_2反演的先验值,避免了因偏差过大而导致的运算结果无法接近真值;基于3层PPDF模型,解决了薄卷云和气溶胶散射引起的光子路径变化而导致的吸收谱线变化的问题。结果表明,PCA方法和PPDF方法联合反演的反演精度得到明显提高;对2013年塔克拉玛干沙漠GOSAT数据的反演结果进行分析,采用单一的PPDF方法得到的反演结果的方差为3.5,两种方法相结合得到的反演结果的方差为1.4,优于日本国立环境研究所(NIES)提供的反演方差(1.6)。In order to study climate change, high-precision measurement for carbon dioxide （CO2） by remote sensing satellite needs to be achieved. Scattering of aerosol and thin cirrus with high transmittance is the main environmental factor which affects CO2 retrieval precision. We combine statistical method of principal component analysis （PCA）with optical path probability density distribution function （PPDF）. Priori values for CO2 retrieval can be obtained by PCA method, and large deviation which causes the problem that calculation results deviate from the truth value can be avoided. We also use three-layer PPDF model to approach the change of absorption spectral lines caused by variation of photon path because of scattering of thin cirrus and aerosol. The results show that the combination of PCA method and PPDF method improves the retrieval precision significantly. From the retrieval results of GOSAT data in Taklamakan desert in 2013, we can find that the variance is 3.5 by PPDF method, while the combination of two methods can obtain the variance of 1.4, which is superior to the variance of 1.6 provided by NIES.

关 键 词：大气光学 二氧化碳反演 光程概率分布的密度函数方法 主成分分析方法 薄卷云和气溶胶散射 

分 类 号：P413[天文地球—大气科学及气象学]