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TanSat is the 1st Chinese carbon dioxide (CO2) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL‐FP) algorithm is implemented for TanSat nadir mode XCO2 retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8th order Fourier series. The spectrum‐correction model and its a priori parameters are developed by analyzing the solar calibration measurement. This correction provides a significant improvement to the O2 A band retrieval. Accordingly, we extend the previous TanSat single CO2 weak band retrieval to a combined O2 A and CO2 weak band retrieval. A Genetic Algorithm (GA) has been applied to determine the threshold values of post‐screening filters. In total, 18.3% of the retrieved data is identified as high quality compared to the original measurements. The same quality control parameters have been used in a footprint independent multiple linear regression bias correction due to the strong correlation with the XCO2 retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO2 retrieval. We show that our new approach produces a significant improvement on the XCO2 retrieval accuracy and precision when compared to TCCON with an average bias and RMSE of −0.08 ppm and 1.47 ppm, respectively. The methods used in this study can help to improve the XCO2 retrieval from TanSat and subsequently the Level‐2 data production, and hence will be applied in the TanSat operational XCO2 processing. Key Points: First using O2 A and 1.61 um CO2 band approaching TanSat XCO2 retreivalDevelopment a method on radiometric correction of TanSat L1B data in O2 A and 1.61 um CO2Validation of new TanSat retrieval against TCCON and recived significant improved results compare to previously retrieval [ABSTRACT FROM AUTHOR]

Top‐down estimates of CO2 fluxes are typically constrained by either surface‐based or space‐based CO2 observations. Both of these measurement types have spatial and temporal gaps in observational coverage that can lead to differences in inferred fluxes. Assimilating both surface‐based and space‐based measurements concurrently in a flux inversion framework improves observational coverage and reduces sampling related artifacts. This study examines the consistency of flux constraints provided by these different observations and the potential to combine them by performing a series of 6‐year (2010–2015) CO2 flux inversions. Flux inversions are performed assimilating surface‐based measurements from the in situ and flask network, measurements from the Total Carbon Column Observing Network (TCCON), and space‐based measurements from the Greenhouse Gases Observing Satellite (GOSAT), or all three data sets combined. Combining the data sets results in more precise flux estimates for subcontinental regions relative to any of the data sets alone. Combining the data sets also improves the accuracy of the posterior fluxes, based on reduced root‐mean‐square differences between posterior flux‐simulated CO2 and aircraft‐based CO2 over midlatitude regions (0.33–0.56 ppm) in comparison to GOSAT (0.37–0.61 ppm), TCCON (0.50–0.68 ppm), or in situ and flask measurements (0.46–0.56 ppm) alone. These results suggest that surface‐based and GOSAT measurements give complementary constraints on CO2 fluxes in the northern extratropics and can be combined in flux inversions to improve constraints on regional fluxes. This stands in contrast with many earlier attempts to combine these data sets and suggests that improvements in the NASA Atmospheric CO2 Observations from Space (ACOS) retrieval algorithm have significantly improved the consistency of space‐based and surface‐based flux constraints. Key Points: Consistent flux constraints are provided by surface in situ and flask, TCCON, and GOSAT measurements of atmospheric CO2Combining data sets improves agreement between modeled and measured aircraft‐based CO2 measurementsImprovements in NASA ACOS retrieval explain improved consistency of space‐based and surface‐based CO2 [ABSTRACT FROM AUTHOR]