Analysis evaluation of near-infrared spectral sensitivity in ground-based XCO2 retrieval using ground-based observations

Abstract

Atmospheric XCO2 (column-averaged dry air mole fractions of atmospheric carbon dioxide) observed by ground-based instruments is one of the important data sources for validating and improving XCO2 retrievals from satellite observations. In this study, Ground-based observations of XCO2 were carried out at the grasslands in Xilinhot, Inner Mongolia of China and Yanting Agro-ecological Experimental Station of Purple Soil, Sichuan of China, by using a ground-based observation system mainly consisting of an optical spectrum analyzer (OSA) and a sun tracker. From the observed solar spectral intensity data, XCO2 data were derived using the Least Squares Matching algorithm applied to the near-infrared spectral data obtained around 1.6µm wavelength and the spectrum simulated based on HITRAN08, as well as concerning with the spectral absorption features of atmospheric CO 2 and the effect of Fraunhofer lines. In the process of XCO2 retrieval, we evaluated the effects of used meteorological parameters on retrieving XCO2. The results show that the spectral transmittance in the wavelength of 6357–6358cm−1, 6360–6361cm−1, and 6363–6364cm−1 is sensitive to the meteorological parameters, and the uncertainty of meteorological parameters lead to an up to 4ppm bias of XCO2 retrievals. These results can be used as references for the optimal spectral selection and retrieval algorithm improvement of ground-based XCO2 observation.