Development of China's atmospheric environment monitoring satellite CO2 IPDA lidar retrieval algorithm based on airborne campaigns

Abstract

China successfully launched the Atmospheric Environment Monitoring Satellite (AEMS) equipped with an Atmospheric Carbon Dioxide Lidar (ACDL) on April 16, 2022, which is the world's first satellite based on Integrated Path Differential Absorption (IPDA) technique to detect the atmospheric CO2 column-weighted dry-air mixing ratio (XCO2). In order to accurately and quickly process the AEMS measurements, we proposed a systematic retrieval algorithm for the AEMS ACDL and conducted two airborne campaigns to validate its performance. The first airborne campaign was conducted in the land-sea interface region of northeast China in 2019. The CO2 retrieval algorithm distinguished significant horizontal XCO2 gradients over different underlying surfaces and obtained an apparent XCO2 enhancement of 8–18 ppm between the urban and forests. The CO2 retrievals not only demonstrated the excellent detection capability of the ACDL for carbon sources and sinks, but also proved the feasibility of the retrieval algorithm in complex terrain and variable atmospheric conditions. The second airborne experiment was conducted in 2021 in the interior desert region of China, which is an excellent flight field to explore the accuracy and precision limits of the retrieval algorithm. We validated the XCO2 retrievals with the airborne in-situ CO2 profiles and demonstrated that the XCO2 accuracy and precision were 0.29 ppm and 0.63 ppm with 1.5-km averages over the desert surface, indicating the accuracy of the retrieval algorithm. The hard target elevation (HTE) retrieval validation results indicate that the IPDA lidar ranging precision is 0.69 m and 6.29 m for the ocean and land surface, respectively. In addition, further analysis combined with the space-borne IPDA lidar simulator showed high consistency in CO2 precision between airborne measurements and simulation results in East Asia, demonstrating the robustness of the retrieval algorithm at continental scales.