The influence of aerosol scattering on XCO2 retrieval accuracy from near-infrared satellite spectra

The main difficulty in satellite retrieval of XCO2 (the dry air column averaged mixing ratio of Carbon dioxide) from near-infrared spectra comes from the uncertainty of light path change brought by scattering of the atmospheric aerosols. The scattering effect described by different aerosol models and surface reflectances may lead to different light path change. This study aims to investigate the influence of neglecting aerosol scattering on CO2 retrieval accuracy for different aerosol models. It is found that for rural, tropospheric and marine aerosol models, the neglecting of aerosol scattering results in underestimation of CO2 retrievals at low surface reflectances (<0.1), but overestimation at surface reflectance over 0.1 and the retrieval errors increase with increasing surface reflectances. For urban aerosol model, the neglecting of aerosol scattering results in underestimation of CO2 retrievals at any surface reflection, and the retrieval errors decrease with increasing surface reflectances. For typical imaging geometry, a surface reflectance of 0.1-0.3 at 1.6μm and AOD(Aerosol Optical Depth) of 0.1-0.3 at 550nm, the neglecting of aerosol scattering leads to retrieval errors of (-0.1%) - (-0.5%), 0.22%-1.92%, 0.09%-1.46% and 0.02%-0.45% for urban, marine, rural and tropospheric aerosol models respectively. XCO2 was retrieved from GOSAT observations with in-situ measured aerosol properties during the Dunhuang2013 field experiment as input. Comparison with ground-based XCO2 measurements shows that the retrieved XCO2 (390.95ppm) is more consistent with the measured XCO2 (390.737ppm) as compared to that of GOSAT L2 product (389.814ppm). Comparison of XCO2retrieved from GOSAT measurements with in-situ measured AOD and the assumption of different aerosol models shows that the assumption of urban and marine aerosol models results in the maximum error of -1.97ppm and 1.58ppm respectively, while the rural aerosol model corresponds to the minimum error of 0.48ppm, which is mainly attributed to little difference between SSA (~0.01) of rural aerosol model and the in-situ measurements.