Articles | Volume 17, issue 7
https://doi.org/10.5194/amt-17-1879-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-1879-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Apr 2024
Research article |
| 03 Apr 2024
| 03 Apr 2024
Aerosol and cloud data processing and optical property retrieval algorithms for the spaceborne ACDL/DQ-1
Guangyao Dai
College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao, 266100, China
Songhua Wu
CORRESPONDING AUTHOR
College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao, 266100, China
Laoshan Laboratory, Qingdao, 266200, China
Institute for Advanced Ocean Study, Ocean University of China, Qingdao, 266100, China
Wenrui Long
College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao, 266100, China
Jiqiao Liu
Key Laboratory of Space Laser Communication and Detection Technology, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, 201800, China
Yuan Xie
Key Laboratory of Space Laser Communication and Detection Technology, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, 201800, China
Kangwen Sun
College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao, 266100, China
Fanqian Meng
College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao, 266100, China
Xiaoquan Song
College of Marine Technology, Faculty of Information Science and Engineering, Ocean University of China, Qingdao, 266100, China
Laoshan Laboratory, Qingdao, 266200, China
Zhongwei Huang
Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China
Weibiao Chen
Key Laboratory of Space Laser Communication and Detection Technology, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, 201800, China
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Cited
11 citations as recorded by crossref.
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- 风云第三代极轨卫星测风激光雷达仿真与指标分析（特邀） 吴. Wu Songhua et al. 10.3788/AOS240800
- Spaceborne high-spectral-resolution lidar ACDL/DQ-1 measurements of the particulate backscatter coefficient in the global ocean Y. Yang et al. 10.1016/j.rse.2024.114444
- Simulation and assessment of spaceborne hybrid Doppler wind lidar, part 1: the spaceborne two-beam stepping direct detection Doppler wind lidar W. Long et al. 10.1364/OE.551023
- Statistical Simulation of Spaceborne Lidar Pulse Propagation in Cirrus Clouds Taking into Account Multiple Scattering T. Russkova & V. Shishko 10.1134/S1024856024701057
- 基于陆地生态系统碳监测卫星的气溶胶光学参数反演与验证研究 陈. Chen Binglong et al. 10.3788/LOP241255
- Performance of the ultraviolet laser transmitter during ESA’s Doppler wind lidar mission Aeolus O. Lux et al. 10.1364/AO.544577
- A Deep Learning Lidar Denoising Approach for Improving Atmospheric Feature Detection P. Selmer et al. 10.3390/rs16152735
- Validation of initial observation from the first spaceborne high-spectral-resolution lidar with a ground-based lidar network Q. Liu et al. 10.5194/amt-17-1403-2024
- Aerosol optical property measurement using the orbiting high-spectral-resolution lidar on board the DQ-1 satellite: retrieval and validation C. Zha et al. 10.5194/amt-17-4425-2024
- Monitoring biomass burning aerosol transport using CALIOP observations and reanalysis models: a Canadian wildfire event in 2019 X. Shang et al. 10.5194/acp-24-1329-2024
7 citations as recorded by crossref.
- The EarthCARE lidar cloud and aerosol profile processor (A-PRO): the A-AER, A-EBD, A-TC, and A-ICE products D. Donovan et al. 10.5194/amt-17-5301-2024
- 风云第三代极轨卫星测风激光雷达仿真与指标分析（特邀） 吴. Wu Songhua et al. 10.3788/AOS240800
- Spaceborne high-spectral-resolution lidar ACDL/DQ-1 measurements of the particulate backscatter coefficient in the global ocean Y. Yang et al. 10.1016/j.rse.2024.114444
- Simulation and assessment of spaceborne hybrid Doppler wind lidar, part 1: the spaceborne two-beam stepping direct detection Doppler wind lidar W. Long et al. 10.1364/OE.551023
- Statistical Simulation of Spaceborne Lidar Pulse Propagation in Cirrus Clouds Taking into Account Multiple Scattering T. Russkova & V. Shishko 10.1134/S1024856024701057
- 基于陆地生态系统碳监测卫星的气溶胶光学参数反演与验证研究 陈. Chen Binglong et al. 10.3788/LOP241255
- Performance of the ultraviolet laser transmitter during ESA’s Doppler wind lidar mission Aeolus O. Lux et al. 10.1364/AO.544577
4 citations as recorded by crossref.
- A Deep Learning Lidar Denoising Approach for Improving Atmospheric Feature Detection P. Selmer et al. 10.3390/rs16152735
- Validation of initial observation from the first spaceborne high-spectral-resolution lidar with a ground-based lidar network Q. Liu et al. 10.5194/amt-17-1403-2024
- Aerosol optical property measurement using the orbiting high-spectral-resolution lidar on board the DQ-1 satellite: retrieval and validation C. Zha et al. 10.5194/amt-17-4425-2024
- Monitoring biomass burning aerosol transport using CALIOP observations and reanalysis models: a Canadian wildfire event in 2019 X. Shang et al. 10.5194/acp-24-1329-2024
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Short summary
An overview is given of the main algorithms applied to derive the aerosol and cloud optical property product of the Aerosol and Carbon Detection Lidar (ACDL), which is capable of globally profiling aerosol and cloud optical properties with high accuracy. The paper demonstrates the observational capabilities of ACDL for aerosol and cloud vertical structure and global distribution through two optical property product measurement cases and global aerosol optical depth profile observations.
An overview is given of the main algorithms applied to derive the aerosol and cloud optical...
