Validation of initial observation from the first space-borne high spectral resolution lidar with ground-based lidar network.

On April 16, 2022, China has successfully launched the world's first space-borne high spectral resolution lidar (HSRL), which is called the Aerosol Carbon Detection Lidar (ACDL) onboard the DQ-1 satellite. The ACDL is expected to precisely detect the three-dimensional distribution of aerosol and cloud globally with high spatial-temporal resolutions. To assess the performance of the newly launched satellite lidar, the ACDL retrieved observations were compared with groundbased lidar measurements of atmospheric aerosol and cloud over northwest China from May to July 2022 by the exploitation of the Belt and Road lidar network (BR-lidarnet) initiated by Lanzhou University of China, as well as CALIPSO lidar observations. A total of six cases at daytime and nighttime, including clear days, dust events, and cloudy conditions, were selected for further analysis. Moreover, profiles of total attenuated backscatter coefficient (TABC) and volume depolarization ratio (VDR) at 532 nm measured by the ACDL, CALIPSO lidar and ground-based lidar are compared in detail. Comparison between the 532 nm extinction coefficient and lidar ratio obtained from ACDL HSRL retrieval and the Raman retrieval results obtained from BR-lidarnet. The achieved results revealed that the ACDL observations were in good agreement with the ground-based lidar measurements during dust events with a relative deviation of about -10.5 ± 25.4 % for the TABC and -6.0 ± 38.5 % for the VDR. Additionally, the heights of cloud top and bottom from these two measurements were well matched and comparable. Compared with the observation of CALIPSO, it also shows high consistency. This study proves that the ACDL provides reliable observations of aerosol and cloud in the presence of various climatic conditions, which helps to further evaluate the impacts of aerosol on climate and environment as well as the ecosystem in the future. [ABSTRACT FROM AUTHOR]