monitoringcarbondioxidefromspaceretrievalalgorithmandfluxinversionbasedongosatdataandusingcarbontrackerchina

	monitoringcarbondioxidefromspaceretrievalalgorithmandfluxinversionbasedongosatdataandusingcarbontrackerchina
	Yang Dongxu 1; Zhang Huifang 2; Liu Yi 1; Chen Baozhang 2; Cai Zhaonan 1; Lu Daren 1
刊名	advancesinatmosphericsciences
	2017
卷号	034 期号:008 页码:965
ISSN号	0256-1530
英文摘要	Monitoring atmospheric carbon dioxide（CO_2） from space-borne state-of-the-art hyperspectral instruments can provide a high precision global dataset to improve carbon flux estimation and reduce the uncertainty of climate projection. Here, we introduce a carbon flux inversion system for estimating carbon flux with satellite measurements under the support of ＂The Strategic Priority Research Program of the Chinese Academy of Sciences—Climate Change： Carbon Budget and Relevant Issues＂. The carbon flux inversion system is composed of two separate parts： the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing（IAPCAS）, and Carbon Tracker-China（CT-China）, developed at the Chinese Academy of Sciences. The Greenhouse gases Observing SATellite（GOSAT） measurements are used in the carbon flux inversion experiment. To improve the quality of the IAPCAS-GOSAT retrieval, we have developed a post-screening and bias correction method, resulting in 25%–30% of the data remaining after quality control. Based on these data, the seasonal variation of XCO_2（column-averaged CO_2dry-air mole fraction） is studied, and a strong relation with vegetation cover and population is identified. Then, the IAPCAS-GOSAT XCO_2 product is used in carbon flux estimation by CT-China. The net ecosystem CO_2 exchange is-0.34 Pg C yr~（-1）（±0.08 Pg C yr~（-1））, with a large error reduction of 84%, which is a significant improvement on the error reduction when compared with in situ-only inversion.
语种	英语
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/125062]
专题	中国科学院地理科学与资源研究所
作者单位	1.中国科学院大气物理研究所 2.Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences
推荐引用方式 GB/T 7714	Yang Dongxu,Zhang Huifang,Liu Yi,et al. monitoringcarbondioxidefromspaceretrievalalgorithmandfluxinversionbasedongosatdataandusingcarbontrackerchina[J]. advancesinatmosphericsciences,2017,034(008):965.
APA	Yang Dongxu,Zhang Huifang,Liu Yi,Chen Baozhang,Cai Zhaonan,&Lu Daren.(2017).monitoringcarbondioxidefromspaceretrievalalgorithmandfluxinversionbasedongosatdataandusingcarbontrackerchina.advancesinatmosphericsciences,034(008),965.
MLA	Yang Dongxu,et al."monitoringcarbondioxidefromspaceretrievalalgorithmandfluxinversionbasedongosatdataandusingcarbontrackerchina".advancesinatmosphericsciences 034.008(2017):965.