Articles | Volume 12, issue 7
https://doi.org/10.5194/amt-12-3825-2019
© Author(s) 2019. 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-12-3825-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Jul 2019
Research article |
| 12 Jul 2019
| 12 Jul 2019
Method to retrieve cloud condensation nuclei number concentrations using lidar measurements
Wangshu Tan
Department of Atmospheric and Oceanic Sciences, School of Physics,
Peking University, Beijing 100871, China
Gang Zhao
Department of Atmospheric and Oceanic Sciences, School of Physics,
Peking University, Beijing 100871, China
Yingli Yu
Department of Atmospheric and Oceanic Sciences, School of Physics,
Peking University, Beijing 100871, China
Department of Atmospheric and Oceanic Sciences, School of Physics,
Peking University, Beijing 100871, China
Jian Li
State Key Laboratory of Severe Weather & Key Laboratory of
Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences,
Beijing 100081, China
Ling Kang
State Key Joint Laboratory of Environmental Simulation and Pollution
Control, College of Environmental Science & Engineering, Peking
University, Beijing 100871, China
State Key Joint Laboratory of Environmental Simulation and Pollution
Control, College of Environmental Science & Engineering, Peking
University, Beijing 100871, China
Chunsheng Zhao
Department of Atmospheric and Oceanic Sciences, School of Physics,
Peking University, Beijing 100871, China
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Cited
11 citations as recorded by crossref.
- Predicting cloud condensation nuclei number concentration based on conventional measurements of aerosol properties in the North China Plain Y. Zhang et al. 10.1016/j.scitotenv.2020.137473
- Measurement report: In situ vertical profiles of below-cloud aerosol over the central Greenland Ice Sheet H. Guy et al. 10.5194/acp-24-11103-2024
- Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data Y. Zhang et al. 10.3390/rs13214396
- Retrieval of particle size distribution based on a multi-objective genetic algorithm for multi-wavelength lidar J. Bao et al. 10.3389/fenvs.2023.1136411
- Profiling Aerosol Liquid Water Content Using a Polarization Lidar W. Tan et al. 10.1021/acs.est.9b07502
- Understanding Aerosol–Cloud Interactions through Lidar Techniques: A Review F. Cairo et al. 10.3390/rs16152788
- Particle number size distribution of PM1 and PM10 in fogs and implications on fog droplet evolutions S. Wu et al. 10.1016/j.atmosenv.2022.119086
- Potential of Polarization Lidar to Profile the Urban Aerosol Phase State during Haze Episodes W. Tan et al. 10.1021/acs.estlett.9b00695
- Multiwavelength Raman lidar system for profiling the CCN number concentrations J. Mao et al. 10.1364/AO.538248
- A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations P. Patel et al. 10.5194/acp-24-2861-2024
- Measurement report: Size-resolved mass concentration of equivalent black carbon-containing particles larger than 700 nm and their role in radiation W. Zhao et al. 10.5194/acp-23-14889-2023
11 citations as recorded by crossref.
- Predicting cloud condensation nuclei number concentration based on conventional measurements of aerosol properties in the North China Plain Y. Zhang et al. 10.1016/j.scitotenv.2020.137473
- Measurement report: In situ vertical profiles of below-cloud aerosol over the central Greenland Ice Sheet H. Guy et al. 10.5194/acp-24-11103-2024
- Retrieval of Water Cloud Optical and Microphysical Properties from Combined Multiwavelength Lidar and Radar Data Y. Zhang et al. 10.3390/rs13214396
- Retrieval of particle size distribution based on a multi-objective genetic algorithm for multi-wavelength lidar J. Bao et al. 10.3389/fenvs.2023.1136411
- Profiling Aerosol Liquid Water Content Using a Polarization Lidar W. Tan et al. 10.1021/acs.est.9b07502
- Understanding Aerosol–Cloud Interactions through Lidar Techniques: A Review F. Cairo et al. 10.3390/rs16152788
- Particle number size distribution of PM1 and PM10 in fogs and implications on fog droplet evolutions S. Wu et al. 10.1016/j.atmosenv.2022.119086
- Potential of Polarization Lidar to Profile the Urban Aerosol Phase State during Haze Episodes W. Tan et al. 10.1021/acs.estlett.9b00695
- Multiwavelength Raman lidar system for profiling the CCN number concentrations J. Mao et al. 10.1364/AO.538248
- A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations P. Patel et al. 10.5194/acp-24-2861-2024
- Measurement report: Size-resolved mass concentration of equivalent black carbon-containing particles larger than 700 nm and their role in radiation W. Zhao et al. 10.5194/acp-23-14889-2023
Latest update: 23 Nov 2024
Short summary
A new method to retrieve CCN number concentrations using multiwavelength Raman lidars is proposed. The method implements hygroscopic enhancements of backscatter and extinction with relative humidity to represent particle hygroscopicity. The retrieved CCN number concentrations are in good agreement with theoretical calculated values. Sensitivity tests indicate that retrieval error in CCN arises mostly from uncertainties in extinction coefficients and RH profiles.
A new method to retrieve CCN number concentrations using multiwavelength Raman lidars is...
