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Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction
Aerosol–cloud interaction (ACI) is complex and difficult to be well represented in current climate models. Progress on understanding ACI processes, such as the influence of aerosols on water cloud droplet formation, is hampered by inadequate observational capability. Hitherto, high-resolution and si...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8915832/ https://www.ncbi.nlm.nih.gov/pubmed/35235447 http://dx.doi.org/10.1073/pnas.2110756119 |
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author | Wang, Nanchao Zhang, Kai Shen, Xue Wang, Yuan Li, Jing Li, Chengcai Mao, Jietai Malinka, Aleksey Zhao, Chuanfeng Russell, Lynn M. Guo, Jianping Gross, Silke Liu, Chong Yang, Jing Chen, Feitong Wu, Lingyun Chen, Sijie Ke, Ju Xiao, Da Zhou, Yudi Fang, Jing Liu, Dong |
author_facet | Wang, Nanchao Zhang, Kai Shen, Xue Wang, Yuan Li, Jing Li, Chengcai Mao, Jietai Malinka, Aleksey Zhao, Chuanfeng Russell, Lynn M. Guo, Jianping Gross, Silke Liu, Chong Yang, Jing Chen, Feitong Wu, Lingyun Chen, Sijie Ke, Ju Xiao, Da Zhou, Yudi Fang, Jing Liu, Dong |
author_sort | Wang, Nanchao |
collection | PubMed |
description | Aerosol–cloud interaction (ACI) is complex and difficult to be well represented in current climate models. Progress on understanding ACI processes, such as the influence of aerosols on water cloud droplet formation, is hampered by inadequate observational capability. Hitherto, high-resolution and simultaneous observations of diurnal aerosol loading and cloud microphysical properties are challenging for current remote-sensing techniques. To overcome this conundrum, we introduce the dual-field-of-view (FOV) high-spectral-resolution lidar (HSRL) for simultaneously profiling aerosol and water cloud properties, especially water cloud microphysical properties. Continuous observations of aerosols and clouds using this instrument, verified by the Monte Carlo simulation and coincident observations of other techniques, were conducted to investigate the interactions between aerosol loading and water cloud microphysical properties. A case study over Beijing highlights the scientific potential of dual-FOV HSRL to become a significant contributor to the ACI investigations. The observed water cloud profiles identify that due to air entrainment its vertical structure is not perfectly adiabatic, as assumed by many current retrieval methods. Our ACI analysis shows increased aerosol loading led to increased droplet number concentration and decreased droplet effective radius—consistent with expectations—but had no discernible increase on liquid water path. This finding supports the hypothesis that aerosol-induced cloud water increase caused by suppressed rain formation can be canceled out by enhanced evaporation. Thus, these observations obtained from the dual-FOV HSRL constitute substantial and significant additions to understanding ACI process. This technique is expected to represent a significant step forward in characterizing ACI. |
format | Online Article Text |
id | pubmed-8915832 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | National Academy of Sciences |
record_format | MEDLINE/PubMed |
spelling | pubmed-89158322022-03-12 Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction Wang, Nanchao Zhang, Kai Shen, Xue Wang, Yuan Li, Jing Li, Chengcai Mao, Jietai Malinka, Aleksey Zhao, Chuanfeng Russell, Lynn M. Guo, Jianping Gross, Silke Liu, Chong Yang, Jing Chen, Feitong Wu, Lingyun Chen, Sijie Ke, Ju Xiao, Da Zhou, Yudi Fang, Jing Liu, Dong Proc Natl Acad Sci U S A Physical Sciences Aerosol–cloud interaction (ACI) is complex and difficult to be well represented in current climate models. Progress on understanding ACI processes, such as the influence of aerosols on water cloud droplet formation, is hampered by inadequate observational capability. Hitherto, high-resolution and simultaneous observations of diurnal aerosol loading and cloud microphysical properties are challenging for current remote-sensing techniques. To overcome this conundrum, we introduce the dual-field-of-view (FOV) high-spectral-resolution lidar (HSRL) for simultaneously profiling aerosol and water cloud properties, especially water cloud microphysical properties. Continuous observations of aerosols and clouds using this instrument, verified by the Monte Carlo simulation and coincident observations of other techniques, were conducted to investigate the interactions between aerosol loading and water cloud microphysical properties. A case study over Beijing highlights the scientific potential of dual-FOV HSRL to become a significant contributor to the ACI investigations. The observed water cloud profiles identify that due to air entrainment its vertical structure is not perfectly adiabatic, as assumed by many current retrieval methods. Our ACI analysis shows increased aerosol loading led to increased droplet number concentration and decreased droplet effective radius—consistent with expectations—but had no discernible increase on liquid water path. This finding supports the hypothesis that aerosol-induced cloud water increase caused by suppressed rain formation can be canceled out by enhanced evaporation. Thus, these observations obtained from the dual-FOV HSRL constitute substantial and significant additions to understanding ACI process. This technique is expected to represent a significant step forward in characterizing ACI. National Academy of Sciences 2022-03-02 2022-03-08 /pmc/articles/PMC8915832/ /pubmed/35235447 http://dx.doi.org/10.1073/pnas.2110756119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Physical Sciences Wang, Nanchao Zhang, Kai Shen, Xue Wang, Yuan Li, Jing Li, Chengcai Mao, Jietai Malinka, Aleksey Zhao, Chuanfeng Russell, Lynn M. Guo, Jianping Gross, Silke Liu, Chong Yang, Jing Chen, Feitong Wu, Lingyun Chen, Sijie Ke, Ju Xiao, Da Zhou, Yudi Fang, Jing Liu, Dong Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction |
title | Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction |
title_full | Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction |
title_fullStr | Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction |
title_full_unstemmed | Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction |
title_short | Dual-field-of-view high-spectral-resolution lidar: Simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction |
title_sort | dual-field-of-view high-spectral-resolution lidar: simultaneous profiling of aerosol and water cloud to study aerosol–cloud interaction |
topic | Physical Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8915832/ https://www.ncbi.nlm.nih.gov/pubmed/35235447 http://dx.doi.org/10.1073/pnas.2110756119 |
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