基于GF-5卫星遥感数据的大气CO_(2)快速反演方法  

Fast Retrieval Method of Atmospheric CO_(2)Based on GF-5 Satellite Remote Sensing Data

作　　者：孙志强 王先华 叶函函 李超 安源[2,3] 孙二昌 吴时超 施海亮 Sun Zhiqiang;Wang Xianhua;Ye Hanhan;Li Chao;An Yuan;Sun Erchang;Wu Shichao;Shi Hailiang(Institutes of Physical Science and Information Technology,Anhui University,Hefei 230601,Anhui,China;Key Laboratory of Optical Calibration and Characterization,Anhui Institute of Optics and Fine Mechanics,Hefei Institutes of Physical Science,Chinese Academy of Sciences,Hefei 230031,Anhui,China;University of Science and Technology of China,Hefei 230026,Anhui,China)

机构地区：[1]安徽大学物质科学与信息技术研究院,安徽合肥230601 [2]中国科学院合肥物质科学研究院安徽光学精密机械研究所通用光学定标与表征技术重点实验室,安徽合肥230031 [3]中国科学技术大学,安徽合肥230026

出　　处：《光学学报》2024年第18期273-282,共10页Acta Optica Sinica

基　　金：国家重点研发计划(2021YFE0118000);国家自然科学基金青年基金(42205146)。

摘　　要：以高分五号卫星(GF-5)搭载的大气温室气体监测仪(GMI)的观测数据为研究对象,设计一种大气CO_(2)快速反演算法,在物理反演算法框架基础上,利用逐线积分法构建适用GMI的气体吸收截面查找表,加速气体吸收光学厚度计算,并通过构建气溶胶光学厚度参数查找表,拟合计算气溶胶光学厚度廓线,从而实现大气CO_(2)快速反演。在此基础上,利用两年的GMI数据验证所提反演算法,并与全球总碳柱观测网(TCCON)站点观测结果进行对比。结果表明,所提出的加速算法与原始算法反演所得的大气CO_(2)柱浓度之间的平均绝对误差为0.75×10^(-6),相关性达到85.5%,与TCCON站点之间平均绝对误差为3.01×10^(-6),满足1%的反演精度要求,在计算效率上,加速算法减少80%以上的计算时间。Objective Since the industrialization era,with the continuously growing industrialization,urbanization,and energy consumption,greenhouse gas emissions have risen sharply,thus causing a constant increase in global temperatures.Atmospheric CO_(2)is a crucial factor in global warming,and as a major anthropogenic greenhouse gas emission,it has caught continuous attention from the international community.Current high-precision CO_(2)observations primarily rely on ground-based measurements and satellite remote sensing.While ground-based observations have advantages such as high accuracy and strong reliability,they are essentially single-point measurements and sparsely distributed globally,unable to provide detection on a global scale.Therefore,atmospheric CO_(2)satellite remote sensing has become the main method for high-precision CO_(2)monitoring on a global scale.However,with the development of satellite remote sensing from discrete to imaging observation techniques,there has been a substantial increase in remote sensing data volume,and existing retrieval algorithms struggle to meet computational time requirements.In our study,we propose a fast retrieval method for atmospheric CO_(2).By constructing a suitable look-up table to replace the time-consuming components in the original algorithm,we aim to achieve fast atmospheric CO_(2)retrieval.Methods We focus on the observational data from China’s Gaofen-5 satellite(GF-5),equipped with the greenhouse gas monitoring instrument(GMI),and present a fast retrieval algorithm for atmospheric CO_(2).First,by leveraging the spectral characteristics of GMI,a line-by-line integration method is employed to construct a gas absorption cross-section look-up table suitable for GMI data,thereby expediting the calculation of gas absorption optical thickness.Secondly,via adopting data from the Modern-Era Retrospective analysis for Research and Applications,Version 2(MERRA-2),and based on Gaussian line shapes,fitting is performed on aerosol optical thickness profiles to establish a look-

关 键 词：大气光学 高分五号卫星气体检测仪 XCO_(2) 快速反演算法 气体吸收截面 气溶胶光学厚度 查找表 

分 类 号：P407[天文地球—大气科学及气象学]