Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration
Abstract Aerosols and clouds greatly affect the Earth’s radiation budget and global climate. Light detection and ranging (lidar) has been recognized as a promising active remote sensing technique for the vertical observations of aerosols and clouds. China launched its first space-borne aerosol-cloud...
| Main Authors: | , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2022-07-01
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| Series: | PhotoniX |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s43074-022-00063-3 |
| _version_ | 1811222978871951360 |
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| author | Ju Ke Yingshan Sun Changzhe Dong Xingying Zhang Zijun Wang Liqing Lyu Wei Zhu Albert Ansmann Lin Su Lingbing Bu Da Xiao Shuaibo Wang Sijie Chen Jiqiao Liu Weibiao Chen Dong Liu |
| author_facet | Ju Ke Yingshan Sun Changzhe Dong Xingying Zhang Zijun Wang Liqing Lyu Wei Zhu Albert Ansmann Lin Su Lingbing Bu Da Xiao Shuaibo Wang Sijie Chen Jiqiao Liu Weibiao Chen Dong Liu |
| author_sort | Ju Ke |
| collection | DOAJ |
| description | Abstract Aerosols and clouds greatly affect the Earth’s radiation budget and global climate. Light detection and ranging (lidar) has been recognized as a promising active remote sensing technique for the vertical observations of aerosols and clouds. China launched its first space-borne aerosol-cloud high-spectral-resolution lidar (ACHSRL) on April 16, 2022, which is capable for high accuracy profiling of aerosols and clouds around the globe. This study presents a retrieval algorithm for aerosol and cloud optical properties from ACHSRL which were compared with the end-to-end Monte-Carlo simulations and validated with the data from an airborne flight with the ACHSRL prototype (A2P) instrument. Using imaging denoising, threshold discrimination, and iterative reconstruction methods, this algorithm was developed for calibration, feature detection, and extinction coefficient (EC) retrievals. The simulation results show that 95.4% of the backscatter coefficient (BSC) have an error less than 12% while 95.4% of EC have an error less than 24%. Cirrus and marine and urban aerosols were identified based on the airborne measurements over different surface types. Then, comparisons were made with U.S. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) profiles, Moderate-resolution Imaging Spectroradiometer (MODIS), and the ground-based sun photometers. High correlations (R > 0.79) were found between BSC (EC) profiles of A2P and CALIOP over forest and town cover, while the correlation coefficients are 0.57 for BSC and 0.58 for EC over ocean cover; the aerosol optical depth retrievals have correlation coefficient of 0.71 with MODIS data and show spatial variations consistent with those from the sun photometers. The algorithm developed for ACHSRL in this study can be directly employed for future space-borne high-spectral-resolution lidar (HSRL) and its data products will also supplement CALIOP data coverage for global observations of aerosol and cloud properties. |
| first_indexed | 2024-04-12T08:24:12Z |
| format | Article |
| id | doaj.art-3d87c3a323f2443f9f413757a5f5cee7 |
| institution | Directory Open Access Journal |
| issn | 2662-1991 |
| language | English |
| last_indexed | 2024-04-12T08:24:12Z |
| publishDate | 2022-07-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | PhotoniX |
| spelling | doaj.art-3d87c3a323f2443f9f413757a5f5cee72022-12-22T03:40:27ZengSpringerOpenPhotoniX2662-19912022-07-013112010.1186/s43074-022-00063-3Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstrationJu Ke0Yingshan Sun1Changzhe Dong2Xingying Zhang3Zijun Wang4Liqing Lyu5Wei Zhu6Albert Ansmann7Lin Su8Lingbing Bu9Da Xiao10Shuaibo Wang11Sijie Chen12Jiqiao Liu13Weibiao Chen14Dong Liu15State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang UniversityState Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang UniversityShanghai Institute of Satellite EngineeringNational Satellite Meteorological Center, China Meteorological AdministrationShanghai Institute of Satellite EngineeringShanghai Academy of Spaceflight TechnologyShanghai Academy of Spaceflight TechnologyLeibniz Institute for Tropospheric Research (TROPOS)Aerospace Information Research Institute, Chinese Academy of SciencesCollaborative Innovation Center On Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and TechnologyState Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang UniversityState Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang UniversityState Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang UniversityShanghai Institute of Optics and Fine Mechanics, Chinese Academy of ScienceShanghai Institute of Optics and Fine Mechanics, Chinese Academy of ScienceState Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering, Zhejiang UniversityAbstract Aerosols and clouds greatly affect the Earth’s radiation budget and global climate. Light detection and ranging (lidar) has been recognized as a promising active remote sensing technique for the vertical observations of aerosols and clouds. China launched its first space-borne aerosol-cloud high-spectral-resolution lidar (ACHSRL) on April 16, 2022, which is capable for high accuracy profiling of aerosols and clouds around the globe. This study presents a retrieval algorithm for aerosol and cloud optical properties from ACHSRL which were compared with the end-to-end Monte-Carlo simulations and validated with the data from an airborne flight with the ACHSRL prototype (A2P) instrument. Using imaging denoising, threshold discrimination, and iterative reconstruction methods, this algorithm was developed for calibration, feature detection, and extinction coefficient (EC) retrievals. The simulation results show that 95.4% of the backscatter coefficient (BSC) have an error less than 12% while 95.4% of EC have an error less than 24%. Cirrus and marine and urban aerosols were identified based on the airborne measurements over different surface types. Then, comparisons were made with U.S. Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) profiles, Moderate-resolution Imaging Spectroradiometer (MODIS), and the ground-based sun photometers. High correlations (R > 0.79) were found between BSC (EC) profiles of A2P and CALIOP over forest and town cover, while the correlation coefficients are 0.57 for BSC and 0.58 for EC over ocean cover; the aerosol optical depth retrievals have correlation coefficient of 0.71 with MODIS data and show spatial variations consistent with those from the sun photometers. The algorithm developed for ACHSRL in this study can be directly employed for future space-borne high-spectral-resolution lidar (HSRL) and its data products will also supplement CALIOP data coverage for global observations of aerosol and cloud properties.https://doi.org/10.1186/s43074-022-00063-3AerosolCloudRetrievalSpace-borne lidarAirborne campaign |
| spellingShingle | Ju Ke Yingshan Sun Changzhe Dong Xingying Zhang Zijun Wang Liqing Lyu Wei Zhu Albert Ansmann Lin Su Lingbing Bu Da Xiao Shuaibo Wang Sijie Chen Jiqiao Liu Weibiao Chen Dong Liu Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration PhotoniX Aerosol Cloud Retrieval Space-borne lidar Airborne campaign |
| title | Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration |
| title_full | Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration |
| title_fullStr | Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration |
| title_full_unstemmed | Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration |
| title_short | Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration |
| title_sort | development of china s first space borne aerosol cloud high spectral resolution lidar retrieval algorithm and airborne demonstration |
| topic | Aerosol Cloud Retrieval Space-borne lidar Airborne campaign |
| url | https://doi.org/10.1186/s43074-022-00063-3 |
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