摘要
基于我国GF-5号卫星上大气温室气体监测仪(GMI)的遥感数据,开展中国区域的CO_(2)反演实验,根据中国区域特征差异对CO_(2)廓线样本进行统计,构建了适合中国区域特征、具有代表性的样本集,然后将统计反演得到的CO_(2)廓线作为初始值代入物理反演方法当中,形成协同统计和物理方法的新算法。通过分析新算法的反演结果,得出协同反演算法在单独使用物理反演算法的基础上精度提高了47.7%,其反演结果与国际上同类型的卫星OCO-2提供的观测结果的相关性达到88.5%。
This paper carried out CO_(2) inversion experiments based on the remote sensing data from the greenhouse gases monitoring instrument(GMI) on the GF-5 satellite in China, calculated the CO_(2) profile samples according to the differences in China’s regional characteristics, and constructed the representative sample set suitable for China’s regional characteristics. Then, it substituted the CO_(2) profile obtained by statistical inversion as the initial value into the physical inversion method to form a new algorithm for synergistic statistics and physical methods. By analyzing the inversion results of the new algorithm, we conclude that the collaborative inversion algorithm improves the accuracy by 47.7% on the basis of using the physical inversion algorithm alone, and the correlation between the inversion results of the new algorithm and the observation results provided by the international satellite of the same type, OCO-2, reaches 88.5%.
作者
吴时超
王先华
叶函函
李超
安源
王晓迪
Wu Shichao;Wang Xianhua;Ye Hanhan;Li Chao;An Yuan;Wang Xiaodi(Key Laboratory of Optical Calibration and Characterization,Anhui Institute of Optics and Fine Mechanics,Hefei Institutes of Physical Science,Chinese Academy of Sciences,Hefei,Anhui 230031,China;University of Science and Technology of China,Hefei,Anhui 230026,China)
出处
《光学学报》
EI
CAS
CSCD
北大核心
2021年第15期16-22,共7页
Acta Optica Sinica
基金
国家重点研发计划(2017YFB050400,2017YFB0504001)
中国科学院合肥物质科学研究院“十三五”规划重点支持项目(Y73H9P1801)
民用航天技术预先研究项目(多模态大气主要温室气体监测仪)。
关键词
大气光学
大气温室气体监测仪
CO_(2)
协同反演算法
atmospheric optics
greenhouse gases monitoring instrument
CO_(2)
collaborative inversion algorithm
