Potential improvement of XCO₂ retrieval of the OCO-2 by having aerosol information from the A-train satellites

Near-real time observations of aerosol properties could have a potential to improve the accuracy XCO2 retrieval algorithm in operational satellite missions. In this study, we developed (Yonsei Retrieval Algorithm; YCAR) based on Optimal Estimation (OE) method that used information at location Orbiting Carbon Observatory-2 (OCO-2) measurement from co-located Afternoon constellation (A-train) such as Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard and Infrared Pathfinder Observation (CALIPSO) MODerate-resolution Imaging Spectrometer (MODIS) Aqua. Specifically, optical depth, vertical profile, MODIS CALIOP data. We validated results Total Column Observing Network (TCCON) ground-based measurements found general consistency. The impact observed its constraint was examined by tests using different settings. effect additional analyzed connection bias correction process algorithm. YCAR priori loading parameters less made comparable data three four cases subject study. Our work provides evidence supporting algorithms quantitatively presents effectiveness synergic use multiple satellites (e.g. A-train) better treatment information.