气候变化领域集成服务门户(CCPortal): An Efficient Algorithm for Retrieving CO2 in the Atmosphere From Hyperspectral Measurements of Satellites: Application of NLS-4DVar Data Assimilation Method

CCPortal

DOI	10.3389/feart.2021.688542
	An Efficient Algorithm for Retrieving CO2 in the Atmosphere From Hyperspectral Measurements of Satellites: Application of NLS-4DVar Data Assimilation Method
	Jin, Zhe; Tian, Xiangjun; Duan, Minzheng; Han, Rui
通讯作者	Tian, XJ (通讯作者)
发表日期	2021
EISSN	2296-6463
卷号	9
英文摘要	A novel and efficient inverse method, named Nonlinear least squares four-dimensional variational data Assimilation (NLS-4DVar)-based CO2 Retrieval Algorithm (NARA), is proposed for retrieving atmospheric CO2 from the satellite hyperspectral measurements, in which the NLS-4DVar method is used as the optimization method. As the NLS-4DVar method works independently of the tangent linear model and adjoint model, the time-consuming calculation of the weighting function matrix is unnecessary, and the computation complexity is tremendously reduced while maintaining the retrieval accuracy. This is extremely important for space-based CO2 retrievals with large data volumes. Observing system simulation experiments (OSSEs) over four different sites around the world showed that the NARA algorithm could retrieve X (CO2) and CO2 profiles effectively. To further evaluate the NARA algorithm, it was used for real CO2 retrievals from target-mode observations of Orbiting Carbon Observatory-2 (OCO-2) over Lamont, Oklahoma, and Darwin, Australia. The results were compared with that of ground measurements of Total Carbon Column Observing Network (TCCON). The mean difference of X (CO2) between NARA and TCCON over Lamont, from 180 observations, was -0.15 ppmv with a standard deviation (SD) of 0.76 ppmv. Over Darwin, the mean difference, from 180 observations (90 points over land and 90 points over the ocean), is -0.17 ppmv (SD: 1.26 ppmv). The preliminary results showed that the efficient NLS-4DVar-based algorithm could provide great help for satellite remote sensing of CO2, and it may be used as an operational procedure after further and extensive evaluations.
关键词	ORBITING CARBON OBSERVATORY-2 DIOXIDE SCIAMACHY CH4 PERFORMANCE VALIDATION AEROSOL CIRRUS MODEL DOAS
英文关键词	Atmospheric CO2; XCO2; retrieval algorithm; NLS-4DVar; satellite observations; OCO-2
语种	英语
WOS研究方向	Geology
WOS类目	Geosciences, Multidisciplinary
WOS记录号	WOS:000678030500001
来源期刊	FRONTIERS IN EARTH SCIENCE
来源机构	中国科学院青藏高原研究所
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/260261
推荐引用方式 GB/T 7714	Jin, Zhe,Tian, Xiangjun,Duan, Minzheng,et al. An Efficient Algorithm for Retrieving CO2 in the Atmosphere From Hyperspectral Measurements of Satellites: Application of NLS-4DVar Data Assimilation Method[J]. 中国科学院青藏高原研究所,2021,9.
APA	Jin, Zhe,Tian, Xiangjun,Duan, Minzheng,&Han, Rui.(2021).An Efficient Algorithm for Retrieving CO2 in the Atmosphere From Hyperspectral Measurements of Satellites: Application of NLS-4DVar Data Assimilation Method.FRONTIERS IN EARTH SCIENCE,9.
MLA	Jin, Zhe,et al."An Efficient Algorithm for Retrieving CO2 in the Atmosphere From Hyperspectral Measurements of Satellites: Application of NLS-4DVar Data Assimilation Method".FRONTIERS IN EARTH SCIENCE 9(2021).