Global land 1° mapping dataset of XCO2 from satellite observations of GOSAT and OCO-2 from 2009 to 2020

被引:23
|
作者
Sheng, Mengya [1 ,2 ]
Lei, Liping [1 ]
Zeng, Zhao-Cheng [3 ]
Rao, Weiqiang [1 ,2 ]
Song, Hao [4 ]
Wu, Changjiang [1 ,2 ]
机构
[1] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing, Peoples R China
[2] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China
[3] CALTECH, Div Geol & Planetary Sci, Pasadena, CA 91125 USA
[4] China Univ Geosci, Sch Earth Sci, Beijing, Peoples R China
关键词
Global land mapping; atmospheric CO2 column concentration; satellite observation; GOSAT; OCO-2; CO2 TOTAL COLUMNS; CARBON-DIOXIDE; EMISSIONS; ENHANCEMENTS; RETRIEVALS; BIAS;
D O I
10.1080/20964471.2022.2033149
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A global mapping data of atmospheric carbon dioxide (CO2) concentrations can help us to better understand the spatiotemporal variations of CO2 and the driving factors of the variations to support the actions for emissions reduction and control. Greenhouse gases satellites that measure atmospheric CO2, such as the Greenhouse Gases Observing Satellite (GOSAT) and Orbiting Carbon Observatory (OCO-2), have been providing global observations of the column averaged dry-air mole fractions of CO2 (XCO2) since 2009. However, these XCO2 retrievals are irregular in space and time with many gaps. In this paper, we mapped a global spatiotemporally continuous XCO2 dataset (Mapping-XCO2) using the XCO2 retrievals from GOSAT and OCO-2 during the period from April 2009 to December 2020 based on a geostatistical approach that fills those data gaps. The dataset covers a geographic range from 56 degrees S to 65 degrees N and 169 degrees W to 180 degrees E for a 1 degrees grid interval in space and 3-day time interval. The uncertainties of the mapped XCO2 values are generally less than 1.5 parts per million (ppm). The spatiotemporal characteristics of global XCO2 that are revealed by the Mapping-XCO2 are similar to the model data obtained from CarbonTracker. Compared to the ground observations, the overall standard bias is 1.13 ppm. The results indicate that this long-term Mapping-XCO2 dataset can be used to investigate the spatiotemporal variations of global atmospheric XCO2 and can support studies related to the carbon cycle and anthropogenic CO2 emissions.
引用
收藏
页码:180 / 200
页数:21
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