Toward High Precision XCO_2 Retrievals From TanSat Observations: Retrieval Improvement and Validation Against TCCON Measurements

摘要

TanSat is the 1st Chinese carbon dioxide (CO_2) measurement satellite, launched in 2016. In this study, the University of Leicester Full Physics (UoL-FP) algorithm is implemented for TanSat nadir mode XCO_2 retrievals. We develop a spectrum correction method to reduce the retrieval errors by the online fitting of an 8~(th) 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 O_2 A band retrieval. Accordingly, we extend the previous TanSat single CO_2 weak band retrieval to a combined O_2 A and CO_2 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 XCO_2 retrieval error. Twenty sites of the Total Column Carbon Observing Network (TCCON) have been selected to validate our new approach for the TanSat XCO_2 retrieval. We show that our new approach produces a significant improvement on the XCO_2 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 XCO_2 retrieval from TanSat and subsequently the Level-2 data production, and hence will be applied in the TanSat operational XCO_2 processing.