Articles | Volume 19, issue 24
https://doi.org/10.5194/acp-19-15483-2019
© 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/acp-19-15483-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Dec 2019
Research article |
| 18 Dec 2019
| 18 Dec 2019
Estimating cloud condensation nuclei number concentrations using aerosol optical properties: role of particle number size distribution and parameterization
Yicheng Shen
Joint International Research Laboratory of Atmospheric Sciences,
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, 00014 University of Helsinki, Helsinki, Finland
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, 00014 University of Helsinki, Helsinki, Finland
Joint International Research Laboratory of Atmospheric Sciences,
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Atmospheric Composition Research, Finnish Meteorological Institute, 00101 Helsinki, Finland
Joint International Research Laboratory of Atmospheric Sciences,
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Krista Luoma
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, 00014 University of Helsinki, Helsinki, Finland
Helmi Keskinen
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, 00014 University of Helsinki, Helsinki, Finland
Hyytiälä Forestry Field Station, Hyytiäläntie 124, Korkeakoski FI 35500, Finland
Pasi P. Aalto
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, 00014 University of Helsinki, Helsinki, Finland
Xuguang Chi
Joint International Research Laboratory of Atmospheric Sciences,
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Ximeng Qi
Joint International Research Laboratory of Atmospheric Sciences,
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Wei Nie
Joint International Research Laboratory of Atmospheric Sciences,
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Xin Huang
Joint International Research Laboratory of Atmospheric Sciences,
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Tuukka Petäjä
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, 00014 University of Helsinki, Helsinki, Finland
Joint International Research Laboratory of Atmospheric Sciences,
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
Markku Kulmala
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, 00014 University of Helsinki, Helsinki, Finland
Veli-Matti Kerminen
Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, 00014 University of Helsinki, Helsinki, Finland
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Cited
10 citations as recorded by crossref.
- Constraining the Twomey effect from satellite observations: issues and perspectives J. Quaas et al. 10.5194/acp-20-15079-2020
- Cluster Analysis of Submicron Particle Number Size Distributions at the SORPES Station in the Yangtze River Delta of East China L. Chen et al. 10.1029/2020JD034004
- The variation in the particle number size distribution during the rainfall: wet scavenging and air mass changing G. Niu et al. 10.5194/acp-23-7521-2023
- Sensitivity study of the impact of CCN size on simulated ground precipitation for deep convection case N. Kovačević 10.1016/j.atmosenv.2022.119309
- Retrieval of the sea spray aerosol mode from submicron particle size distributions and supermicron scattering during LASIC J. Dedrick et al. 10.5194/amt-15-4171-2022
- Cloud probability distribution of typical urban agglomerations in China based on Sentinel-2 satellite remote sensing J. Ling et al. 10.1016/j.jag.2024.104254
- Particle Number Size Distribution of Wintertime Alpine Aerosols and Their Activation as Cloud Condensation Nuclei in the Guanzhong Plain, Northwest China Y. Chen et al. 10.1029/2022JD037877
- Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within‐The‐Atmosphere Observations: A Three‐Way Street R. Kahn et al. 10.1029/2022RG000796
- Overview: Recent advances in the understanding of the northern Eurasian environments and of the urban air quality in China – a Pan-Eurasian Experiment (PEEX) programme perspective H. Lappalainen et al. 10.5194/acp-22-4413-2022
- Aerosol impacts on summer precipitation forecast over the North China Plain by using Thompson aerosol-aware scheme in WRF: Statistical analysis and significant threat score improvements in polluted condition during June to August 2018 C. Guo et al. 10.1016/j.atmosres.2023.107177
10 citations as recorded by crossref.
- Constraining the Twomey effect from satellite observations: issues and perspectives J. Quaas et al. 10.5194/acp-20-15079-2020
- Cluster Analysis of Submicron Particle Number Size Distributions at the SORPES Station in the Yangtze River Delta of East China L. Chen et al. 10.1029/2020JD034004
- The variation in the particle number size distribution during the rainfall: wet scavenging and air mass changing G. Niu et al. 10.5194/acp-23-7521-2023
- Sensitivity study of the impact of CCN size on simulated ground precipitation for deep convection case N. Kovačević 10.1016/j.atmosenv.2022.119309
- Retrieval of the sea spray aerosol mode from submicron particle size distributions and supermicron scattering during LASIC J. Dedrick et al. 10.5194/amt-15-4171-2022
- Cloud probability distribution of typical urban agglomerations in China based on Sentinel-2 satellite remote sensing J. Ling et al. 10.1016/j.jag.2024.104254
- Particle Number Size Distribution of Wintertime Alpine Aerosols and Their Activation as Cloud Condensation Nuclei in the Guanzhong Plain, Northwest China Y. Chen et al. 10.1029/2022JD037877
- Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within‐The‐Atmosphere Observations: A Three‐Way Street R. Kahn et al. 10.1029/2022RG000796
- Overview: Recent advances in the understanding of the northern Eurasian environments and of the urban air quality in China – a Pan-Eurasian Experiment (PEEX) programme perspective H. Lappalainen et al. 10.5194/acp-22-4413-2022
- Aerosol impacts on summer precipitation forecast over the North China Plain by using Thompson aerosol-aware scheme in WRF: Statistical analysis and significant threat score improvements in polluted condition during June to August 2018 C. Guo et al. 10.1016/j.atmosres.2023.107177
Latest update: 20 Nov 2024
Short summary
Long-term cloud condensation nuclei (CCN) number concentration (NCCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating NCCN from AOP measurements. With the new parameterization NCCN can be estimated from backscatter fraction, scattering Ångström exponent, and total light-scattering coefficient. The NCCN–AOP relationships depend on the geometric mean diameter and the width of the size distribution.
Long-term cloud condensation nuclei (CCN) number concentration (NCCN) data are scarce; there are a...
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