Toward high precision XCO2 retrievals from TanSat observations

TanSat is the 1^st Chinese carbon dioxide measurement satellite, launched in 2016. Preliminary TanSat XCO₂ retrievals have been introduced in previous studies based on the 1.6 m weak CO₂ band. 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 an online fitting of an 8^th order Fourier series. The model and a priori is 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. The same quality control parameters have been used in the bias correction due to the stronger correlation with the XCO₂ retrieval error. A footprint independent multiple linear regression is applied to determine the sounding XCO₂ retrieval error and bias correction. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach of the TanSat XCO₂ retrieval. We show that our new approach produces a significant improvement of the XCO₂ retrieval accuracy and precision when compared with TCCON with an average bias and RMSE of -0.08 and 1.47 ppm respectively. The methods used in this study, such as continuum correction, 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.