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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
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.
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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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