气候变化领域集成服务门户(CCPortal): An inversion model based on GEOS-Chem for estimating global and China's terrestrial carbon fluxes in 2019

CCPortal

DOI	10.1016/j.accre.2023.01.001
	An inversion model based on GEOS-Chem for estimating global and China's terrestrial carbon fluxes in 2019
	Wu, Chong -Yuan; Zhang, Xiao-Ye; Guo, Li-Feng; Zhong, Jun -Ting; Wang, De-Ying; Miao, Chang -Hong; Gao, Xiang; Zhang, Xi-Liang
发表日期	2023
ISSN	1674-9278
起始页码	49
结束页码	61
卷号	14 期号:1 页码:13
英文摘要	The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories added the method of assimilating atmospheric CO2 concentrations to invert carbon sources and sinks; however, many global carbon inversion models are not publicly available. In addition, our regional assimilation inversion system, CCMVS-R (China Carbon Monitoring, Verification and Supporting for Regional), needs a global carbon inversion model with higher assimilation efficiency to provide boundary conditions. Here, an inversion model based on the global atmospheric chemistry model GEOS-Chem and a more accurate and easier-to-implement ensemble square root Kalman filter (EnSRF) algorithm is con-structed and used to infer global and China's carbon fluxes in 2019. Atmospheric CO2 concentrations from ObsPack sites and five additional CO2 observational sites from China's Greenhouse Gas Observation Network (CGHGNET) were used for data assimilation to improve the estimate. The inverted annual global terrestrial and oceanic carbon uptake is 2.12 and 2.53 Pg C per year, respectively, accounting for 21.1% and 25.1% of global fossil fuel CO2 emissions. The remaining 5.41 Pg C per year in the atmosphere is consistent with the global atmospheric CO2 growth rates of 5.44 Pg C per year reported by the National Oceanic and Atmospheric Administration (NOAA), showing that the inversion model can provide a reasonable estimate of global-scale natural carbon sinks. The inverted terrestrial carbon sink of China is 0.37 Pg C per year, accounting for approximately 13% of China's fossil CO2 emissions.
英文关键词	CO2; Data assimilation; EnSRF; GEOS-Chem; Terrestrial carbon fluxes
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000955079900001
来源期刊	ADVANCES IN CLIMATE CHANGE RESEARCH
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273990
作者单位	Chinese Academy of Meteorological Sciences (CAMS); Henan University; Zhejiang University; Tsinghua University
推荐引用方式 GB/T 7714	Wu, Chong -Yuan,Zhang, Xiao-Ye,Guo, Li-Feng,et al. An inversion model based on GEOS-Chem for estimating global and China's terrestrial carbon fluxes in 2019[J],2023,14(1):13.
APA	Wu, Chong -Yuan.,Zhang, Xiao-Ye.,Guo, Li-Feng.,Zhong, Jun -Ting.,Wang, De-Ying.,...&Zhang, Xi-Liang.(2023).An inversion model based on GEOS-Chem for estimating global and China's terrestrial carbon fluxes in 2019.ADVANCES IN CLIMATE CHANGE RESEARCH,14(1),13.
MLA	Wu, Chong -Yuan,et al."An inversion model based on GEOS-Chem for estimating global and China's terrestrial carbon fluxes in 2019".ADVANCES IN CLIMATE CHANGE RESEARCH 14.1(2023):13.