Global land 1° mapping dataset of XCO2 from satellite observations of GOSAT and OCO-2 from 2009 to 2020. Issue 1 (2nd January 2023)

• Record Type: Journal Article
• Authors: Sheng, Mengya; Lei, Liping; Zeng, Zhao-Cheng; Rao, Weiqiang; Song, Hao; Wu, Changjiang
• Is Part Of: Big earth data. Volume 7:Issue 1(2023)
• Page Start: 170
• Page End: 190
• Publication Date: 2023-01-02
• Subjects: Global land mapping -- atmospheric CO2 column concentration -- satellite observation -- GOSAT -- OCO-2; Earth sciences -- Periodicals; Earth sciences -- Research -- Periodicals; Geographic information systems Periodicals; 550
• DOI: 10.1080/20964471.2022.2033149
• Languages: English
• ISSNs: 2096-4471

Abstract

ABSTRACT: 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° S to 65° N and 169° W to 180° E for a 1° 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. The dataset is available at http://www.doi.org/10.7910/DVN/4WDTD8 and https://www.scidb.cn/en/detail?dataSetId=c2c3111b421043fc8d9b163c39e6f56e .