Toward High Precision XCO2 Retrievals from TanSat Observations:
Retrieval Improvement and Validation against TCCON Measurements
Abstract
TanSat is the 1st Chinese carbon dioxide (CO) measurement satellite,
launched in 2016. In this study, the University of Leicester Full
Physics (UoL-FP) algorithm is implemented for TanSat nadir mode XCO
retrievals. We develop a spectrum correction method to reduce the
retrieval errors by the online fitting of an 8 order Fourier series. The
model and a priori is developed by analyzing the solar calibration
measurement. This correction provides a significant improvement to the O
A band retrieval. Accordingly, we extend the previous TanSat single CO
weak band retrieval to a combined O A and CO 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
stronger correlation with the XCO retrieval error. Twenty sites of the
Total Column Carbon Observing Network (TCCON) have been selected to
validate our new approach for the TanSat XCO retrieval. We show that our
new approach produces a significant improvement on the XCO 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 retrieval from TanSat and subsequently
the Level-2 data production, and hence will be applied in the TanSat
operational XCO processing.