THE FUSION ALGORITHM OF XCO2 PRODUCTS: APPLIED TO GOSAT

被引：0
|
作者：
Jin, Chunlin [1 ]
Xue, Yong [1 ,2 ]
Zhao, Liang [1 ]
Jiang, Xingxing [1 ]
Yuan, Tao [1 ]
Sun, Yuxin [1 ]
Wu, Shuhui [1 ]
机构：
[1] China Univ Min & Technol, Sch Environm & Spatial Informat, Xuzhou 221116, Jiangsu, Peoples R China
[2] China Univ Min & Technol, Artificial Intelligence Res Inst, Xuzhou 221116, Jiangsu, Peoples R China
来源：
2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年
基金：
中国国家自然科学基金;
关键词：
GOSAT; XCO2; Fusion; MLE; GLOBAL ATMOSPHERIC CO2;
D O I：
10.1109/IGARSS46834.2022.9884955
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
The Greenhouse Gases Observing Satellite (GOSAT) is the world's first spacecraft to measure the concentrations of CO2 from space and it has highprecision hyperspectral atmospheric CO2 monitoring from 2009. Several atmospheric CO2 products, such as ACOS, NIES, OCFP and SRFP products from full physics retrieval algorithm, both provide XCO2 (the column-average dry-air mole fraction of atmospheric CO2) of GOSAT. These products have different characteristics and advantages and have different performance in different regions. In order to obtain the XCO2 data set with high precision, low uncertainty and high coverage, the maximum likelihood estimation (MLE) method is used to fuse GOSAT XCO2 products. The algorithm takes into account the uncertainty of each product on each pixel, and is applied from April 2009 to December 2015. The validation result between fusion XCO2 and Total Carbon Column Observing Network XCO2 shows R = 0.843 and RMSE = 3.248.
引用
收藏
页码：6630 / 6633
页数：4
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