Abstract
The GOSAT satellite has been designed for retrieving the carbon dioxide amount in the atmosphere by a Fourier transform spectro-radiometer (TANSO-FTS). It is, however, known that FTS-observed radiances in the near-infrared spectral region are heavily contaminated by a solar radiation component scattered by atmospheric aerosols, which is known as “path radiance”. In order to correct the path radiance, a multispectral visible-near infrared imager (TANSO-CAI) will be on board the GOSAT satellite to acquire the aerosol and cloud information that is indispensable for correcting the atmospheric path radiance to improve the carbon dioxide remote sensing by FTS. In this article, we study aerosol retrieval algorithms and cloud screening algorithms using the four channel radiances of CAI. We also present the methodology for vicarious calibration and validation for the CAI remote sensing, intercomparison of CAI-retrieved aerosol products with those from other satellite-borne sensors, and the data fusion strategy of satellite-measured and model-simulated aerosol properties.
