Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data
The remote sensing of water clouds is useful for studying their spatial and temporal variations and constraining physical processes in climate and weather prediction models. However, radar-only detection provides inadequate information for the cloud droplet size distribution. Here, we propose a nove...
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MDPI AG
2021-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/21/4396 |
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| author | Yinchao Zhang Su Chen Wangshu Tan Siying Chen He Chen Pan Guo Zhuoran Sun Rui Hu Qingyue Xu Mengwei Zhang Wei Hao Zhichao Bu |
| author_facet | Yinchao Zhang Su Chen Wangshu Tan Siying Chen He Chen Pan Guo Zhuoran Sun Rui Hu Qingyue Xu Mengwei Zhang Wei Hao Zhichao Bu |
| author_sort | Yinchao Zhang |
| collection | DOAJ |
| description | The remote sensing of water clouds is useful for studying their spatial and temporal variations and constraining physical processes in climate and weather prediction models. However, radar-only detection provides inadequate information for the cloud droplet size distribution. Here, we propose a novel lookup-table method, which combines lidar (1064, 532 nm) and radar (8.6 mm) to retrieve profiles of cloud optical (backscatter coefficient and extinction coefficient) and microphysical properties (effective diameter and liquid water content). Through the iteration of the extinction-to-backscatter ratio, more continuous cloud optical characteristics can be obtained. Sensitivity analysis shows that a 10% error of the lidar constant will lead to a retrieval error of up to 30%. The algorithm performed precise capture of the ideal cloud signal at a specific height and at full height and the maximum relative error of the backscatter coefficients at 1064 nm and 532 nm were 6% and 4%, respectively. With the application of the algorithm in the two observation cases on single or multiple cloud layers, the results indicate that the microphysical properties mostly agree with the empirical radar measurements but are slightly different when larger particles cause signal changes of different extents. Consequently, the synergetic algorithm is capable of computing the cloud droplet size distribution. It provides continuous profiles of cloud optical properties and captures cloud microphysical properties well for water cloud studies. |
| first_indexed | 2024-03-10T05:53:52Z |
| format | Article |
| id | doaj.art-6608d53079ac4735ac7a7e2e43f42fe7 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T05:53:52Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-6608d53079ac4735ac7a7e2e43f42fe72023-11-22T21:32:51ZengMDPI AGRemote Sensing2072-42922021-10-011321439610.3390/rs13214396Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar DataYinchao Zhang0Su Chen1Wangshu Tan2Siying Chen3He Chen4Pan Guo5Zhuoran Sun6Rui Hu7Qingyue Xu8Mengwei Zhang9Wei Hao10Zhichao Bu11School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaSchool of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, ChinaMetrological Observation Centre of the China Meteorological Administration (CMA), Beijing 100081, ChinaThe remote sensing of water clouds is useful for studying their spatial and temporal variations and constraining physical processes in climate and weather prediction models. However, radar-only detection provides inadequate information for the cloud droplet size distribution. Here, we propose a novel lookup-table method, which combines lidar (1064, 532 nm) and radar (8.6 mm) to retrieve profiles of cloud optical (backscatter coefficient and extinction coefficient) and microphysical properties (effective diameter and liquid water content). Through the iteration of the extinction-to-backscatter ratio, more continuous cloud optical characteristics can be obtained. Sensitivity analysis shows that a 10% error of the lidar constant will lead to a retrieval error of up to 30%. The algorithm performed precise capture of the ideal cloud signal at a specific height and at full height and the maximum relative error of the backscatter coefficients at 1064 nm and 532 nm were 6% and 4%, respectively. With the application of the algorithm in the two observation cases on single or multiple cloud layers, the results indicate that the microphysical properties mostly agree with the empirical radar measurements but are slightly different when larger particles cause signal changes of different extents. Consequently, the synergetic algorithm is capable of computing the cloud droplet size distribution. It provides continuous profiles of cloud optical properties and captures cloud microphysical properties well for water cloud studies.https://www.mdpi.com/2072-4292/13/21/4396water cloudradarmultiwavelength lidaroptical propertiesmicrophysical properties |
| spellingShingle | Yinchao Zhang Su Chen Wangshu Tan Siying Chen He Chen Pan Guo Zhuoran Sun Rui Hu Qingyue Xu Mengwei Zhang Wei Hao Zhichao Bu Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data Remote Sensing water cloud radar multiwavelength lidar optical properties microphysical properties |
| title | Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data |
| title_full | Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data |
| title_fullStr | Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data |
| title_full_unstemmed | Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data |
| title_short | Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data |
| title_sort | retrieval of water cloud optical and microphysical properties from combined multiwavelength lidar and radar data |
| topic | water cloud radar multiwavelength lidar optical properties microphysical properties |
| url | https://www.mdpi.com/2072-4292/13/21/4396 |
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