First TanSat CO2 retrieval over land and ocean using both nadir and glint spectroscopy

Abstract

The world is facing a serious warming crisis, highlighting the need for monitoring greenhouse gases such as carbon dioxide (CO2). In 2016, China launched its first satellite mission for measuring atmospheric CO2, i.e., TanSat. Previous TanSat retrievals of the column-averaged dry air mole fraction of CO2 (XCO2) have a moderate precision of 1.47–2.45 ppm, with only limited spatial coverage over the land surface by using TanSat nadir-mode (ND) spectroscopy. These existing gaps are affected by the poor signal-to-noise ratio of glint mode (GL) or over the oceanic surface. However, CO2 measurements over the ocean, a major source of global carbon sinks, are often lacking and subject to significant uncertainties but are nevertheless quite important. To increase the spatial coverage and retrieval accuracy and precision of TanSat CO2, we further improve XCO2 retrieval by introducing spectral recalibration, spectral window optimization, and explicit radiative transfer simulation. Thus, universal CO2 retrieval with high precision over land and ocean is realized by using both ND and GL spectra. Ground-based comparisons using the total carbon column observing network (TCCON) indicate that the standard deviations of the bias-corrected XCO2 retrievals from the ND and GL modes were 1.28 and 1.19 ppm, respectively. Consistent spatial and temporal distributions of satellite XCO2 retrievals can also be found among TanSat, the Greenhouse gases Observing SATellite (GOSAT), and the Orbiting Carbon Observatory-2 (OCO-2) satellites. The updated TanSat XCO2 retrievals have ~3.5 times the seasonal spatial coverage of GOSAT, while the highest difference between TanSat and OCO-2 is only +0.63 ppm. In addition, TanSat XCO2 retrievals over the ocean successfully captured enhanced CO2 plumes from the neighboring Yasur volcano, with an estimated emission flux of 32.1 kilotons per day. These results indicate that the improved TanSat XCO2 retrieval is useful for understanding and quantifying global land and ocean carbon emissions.