Inadequate treatment of aerosol scattering can be a significant source of error when retrieving column-averaged dry-air mole fractions of CO2 (XCO2) from space-based measurements of backscattered solar shortwave radiation. We have developed a retrieval algorithm, RemoTeC, that retrieves three aerosol parameters (amount, size, and height) simultaneously with XCO2. Here we evaluate the ability of RemoTeC to account for light path modifications by clouds, subvisual cirrus, and aerosols when retrieving XCO2 from Greenhouse Gases Observing Satellite (GOSAT) Thermal and Near-infrared Sensor for carbon Observation (TANSO)-Fourier Transform Spectrometer (FTS) measurements. We first evaluate a cloud filter based on measurements from the Cloud and Aerosol Imager and a cirrus filter that uses radiances measured by TANSO-FTS in the 2micron spectral region, with strong water absorption. For the cloud-screened scenes, we then evaluate errors due to aerosols. We find that RemoTeC is well capable of accounting for scattering by aerosols for values of aerosol optical thickness at 750nm up to 0.25. While no significant correlation of errors is found with albedo, correlations are found with retrieved aerosol parameters. To further improve the XCO2 accuracy, we propose and evaluate a bias correction scheme.
Measurements from 12 ground-based stations of the Total Carbon Column Observing Network (TCCON) are used as a reference in this study. We show that spatial colocation criteria may be relaxed using additional constraints based on modeled XCO2 gradients, to increase the size and diversity of validation data and provide a more robust evaluation of GOSAT retrievals. Global-scale validation of satellite data remains challenging and would be improved by increasing TCCON coverage.