Retrieved XCO2 Accuracy Improvement by Reducing Aerosol-Induced Bias for China’s Future High-Precision Greenhouse Gases Monitoring Satellite Mission

Abstract

China is developing the High-precision Greenhouse gases Monitoring Satellite (HGMS), carrying a high-spectral-resolution lidar (HSRL) for aerosol vertical profiles and imaging grating spectrometers for CO2 measurements at the same time. By providing simultaneous evaluation of the aerosol scattering effect, HGMS would reduce the bias of the XCO2 retrievals from the passive sensor. In this work, we propose a method to reduce aerosol-induced bias in XCO2 retrievals for the future HGMS mission based on the correlation analysis among simulated radiance, XCO2 bias, and aerosol optical depth (AOD) ratio. We exercise the method with the Orbiting Carbon Observatory-2 (OCO-2) XCO2 retrievals and AOD ratio inferred from the OCO-2 O2 A-band aerosol parameters at 755 nm and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) AOD at 532 nm at several Total Carbon Column Observing Network (TCCON) sites in Europe. The results showed that 80% of measurements from OCO-2 were improved, and data from six TCCON sites show an average of 2.6 ppm reduction in mean bias and a 68% improvement in accuracy. We demonstrate the advantage of fused active–passive observation of the HGMS for more accurate global XCO2 measurements in the future.