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Validation of GOSAT and OCO-2 against In Situ Aircraft Measurements and Comparison with CarbonTracker and GEOS-Chem over Qinhuangdao, China.

Authors :
Mustafa, Farhan
Wang, Huijuan
Bu, Lingbing
Wang, Qin
Shahzaman, Muhammad
Bilal, Muhammad
Zhou, Minqiang
Iqbal, Rashid
Aslam, Rana Waqar
Ali, Md. Arfan
Qiu, Zhongfeng
Antón, Manuel
Source :
Remote Sensing; 3/1/2021, Vol. 13 Issue 5, p899-899, 1p
Publication Year :
2021

Abstract

Carbon dioxide (CO<subscript>2</subscript>) is the most important greenhouse gas and several satellites have been launched to monitor the atmospheric CO<subscript>2</subscript> at regional and global scales. Evaluation of the measurements obtained from these satellites against accurate and precise instruments is crucial. In this work, aircraft measurements of CO<subscript>2</subscript> were carried out over Qinhuangdao, China (39.9354°N, 119.6005°E), on 14, 16, and 19 March 2019 to validate the Greenhous gases Observing SATellite (GOSAT) and the Orbiting Carbon Observatory 2 (OCO-2) CO<subscript>2</subscript> retrievals. The airborne in situ instruments were mounted on a research aircraft and the measurements were carried out between the altitudes of ~0.5 and 8.0 km to obtain the vertical profiles of CO<subscript>2</subscript>. The profiles captured a decrease in CO<subscript>2</subscript> concentration from the surface to maximum altitude. Moreover, the vertical profiles from GEOS-Chem and the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker were also compared with in situ and satellite datasets. The satellite and the model datasets captured the vertical structure of CO<subscript>2</subscript> when compared with in situ measurements, which showed good agreement among the datasets. The dry-air column-averaged CO<subscript>2</subscript> mole fractions (XCO<subscript>2</subscript>) retrieved from OCO-2 and GOSAT showed biases of 1.33 ppm (0.32%) and −1.70 ppm (−0.41%), respectively, relative to the XCO<subscript>2</subscript> derived from in situ measurements. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
13
Issue :
5
Database :
Complementary Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
149296001
Full Text :
https://doi.org/10.3390/rs13050899