Articles | Volume 15, issue 13
https://doi.org/10.5194/acp-15-7585-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-15-7585-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
13 Jul 2015
Research article |
| 13 Jul 2015
The relationship between cloud condensation nuclei (CCN) concentration and light extinction of dried particles: indications of underlying aerosol processes and implications for satellite-based CCN estimates
Y. Shinozuka
CORRESPONDING AUTHOR
Bay Area Environmental Research Institute, Petaluma, California, USA
NASA Ames Research Center Cooperative for Research in Earth Science and Technology, Moffett Field, California, USA
A. D. Clarke
School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, Hawaii, USA
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
A. Jefferson
Cooperative Institute for Research in Environmental Science (CIRES), University of Colorado, Boulder, Colorado, USA
NOAA Earth System Research Laboratory, Boulder, Colorado, USA
R. Wood
Department of Atmospheric Sciences, University of Washington, Seattle, Washington, USA
C. S. McNaughton
Golder Associates Ltd., Saskatoon, Saskatchewan, Canada
School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, Hawaii, USA
J. Ström
Department of Applied Environmental Science, Stockholm University, Stockholm, Sweden
P. Tunved
Department of Applied Environmental Science, Stockholm University, Stockholm, Sweden
J. Redemann
NASA Ames Research Center, Moffett Field, California, USA
K. L. Thornhill
Science Systems and Applications Inc., Hampton, Virginia, USA
R. H. Moore
NASA Langley Research Center, Hampton, Virginia, USA
T. L. Lathem
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
Phillips 66 Research Center, Bartlesville, Oklahoma, USA
J. J. Lin
School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia, USA
Y. J. Yoon
Korea Polar Research Institute, Yeonsu-Gu, Incheon, Korea
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Cited
73 citations as recorded by crossref.
- Relationship between cloud condensation nuclei (CCN) concentration and aerosol optical depth in the Arctic region S. Ahn et al. https://doi.org/10.1016/j.atmosenv.2021.118748
- Global expansion of the sensitive aerosol-limited marine cloud regime under emission reductions X. Han et al. https://doi.org/10.1126/sciadv.aef9665
- Retrieval and validation of cloud condensation nuclei from satellite and airborne measurements over the Indian Monsoon region A. Aravindhavel et al. https://doi.org/10.1016/j.atmosres.2023.106802
- Interpretable ensemble learning unveils main aerosol optical properties in predicting cloud condensation nuclei number concentration N. Wang et al. https://doi.org/10.1038/s41612-025-01181-y
- Under What Conditions Can We Trust Retrieved Cloud Drop Concentrations in Broken Marine Stratocumulus? Y. Zhu et al. https://doi.org/10.1029/2017JD028083
- Prediction of CCN spectra parameters in the North China Plain using a random forest model M. Liang et al. https://doi.org/10.1016/j.atmosenv.2022.119323
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- Vertical Variability of Temperature and Moisture in a Compound Dust-Heatwave Scenario at South-Western Iberian Peninsula: Implications for Surface Thermal Stress and CCN Predictions C. Córdoba-Jabonero et al. https://doi.org/10.3390/rs18162693
- Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within‐The‐Atmosphere Observations: A Three‐Way Street R. Kahn et al. https://doi.org/10.1029/2022RG000796
- Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship‐based and satellite remote sensing observations D. Painemal et al. https://doi.org/10.1002/2016JD025771
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- POLIPHON conversion factors for retrieving dust-related cloud condensation nuclei and ice-nucleating particle concentration profiles at oceanic sites Y. He et al. https://doi.org/10.5194/amt-16-1951-2023
- Polarimeter + Lidar–Derived Aerosol Particle Number Concentration J. Schlosser et al. https://doi.org/10.3389/frsen.2022.885332
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- Vertical profiles of cloud condensation nuclei number concentration and its empirical estimate from aerosol optical properties over the North China Plain R. Zhang et al. https://doi.org/10.5194/acp-22-14879-2022
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- Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic E. Lenhardt et al. https://doi.org/10.5194/amt-16-2037-2023
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- Satellite‐Based Detection of Secondary Droplet Activation in Convective Clouds A. Efraim et al. https://doi.org/10.1029/2022JD036519
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- Distribution Characteristics of Aerosol Size and CCN during the Summer on Mt. Tian and Their Influencing Factors A. Liu et al. https://doi.org/10.3390/atmos11090912
- Derived Profiles of CCN and INP Number Concentrations in the Taklimakan Desert via Combined Polarization Lidar, Sun-Photometer, and Radiosonde Observations S. Zhang et al. https://doi.org/10.3390/rs15051216
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- Assessment of CALIOP-Derived CCN Concentrations by In Situ Surface Measurements G. Choudhury & M. Tesche https://doi.org/10.3390/rs14143342
73 citations as recorded by crossref.
- Relationship between cloud condensation nuclei (CCN) concentration and aerosol optical depth in the Arctic region S. Ahn et al. https://doi.org/10.1016/j.atmosenv.2021.118748
- Global expansion of the sensitive aerosol-limited marine cloud regime under emission reductions X. Han et al. https://doi.org/10.1126/sciadv.aef9665
- Retrieval and validation of cloud condensation nuclei from satellite and airborne measurements over the Indian Monsoon region A. Aravindhavel et al. https://doi.org/10.1016/j.atmosres.2023.106802
- Interpretable ensemble learning unveils main aerosol optical properties in predicting cloud condensation nuclei number concentration N. Wang et al. https://doi.org/10.1038/s41612-025-01181-y
- Under What Conditions Can We Trust Retrieved Cloud Drop Concentrations in Broken Marine Stratocumulus? Y. Zhu et al. https://doi.org/10.1029/2017JD028083
- Prediction of CCN spectra parameters in the North China Plain using a random forest model M. Liang et al. https://doi.org/10.1016/j.atmosenv.2022.119323
- An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast—Part 2: Circulation, Boundary Layer, and Clouds D. Painemal et al. https://doi.org/10.1029/2020JD033423
- Helicopter-borne observations of the continental background aerosol in combination with remote sensing and ground-based measurements S. Düsing et al. https://doi.org/10.5194/acp-18-1263-2018
- Vertical Variability of Temperature and Moisture in a Compound Dust-Heatwave Scenario at South-Western Iberian Peninsula: Implications for Surface Thermal Stress and CCN Predictions C. Córdoba-Jabonero et al. https://doi.org/10.3390/rs18162693
- Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within‐The‐Atmosphere Observations: A Three‐Way Street R. Kahn et al. https://doi.org/10.1029/2022RG000796
- Aerosol and cloud microphysics covariability in the northeast Pacific boundary layer estimated with ship‐based and satellite remote sensing observations D. Painemal et al. https://doi.org/10.1002/2016JD025771
- A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations F. Alexandri et al. https://doi.org/10.5194/amt-17-1739-2024
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- POLIPHON conversion factors for retrieving dust-related cloud condensation nuclei and ice-nucleating particle concentration profiles at oceanic sites Y. He et al. https://doi.org/10.5194/amt-16-1951-2023
- Polarimeter + Lidar–Derived Aerosol Particle Number Concentration J. Schlosser et al. https://doi.org/10.3389/frsen.2022.885332
- Aerosol optical-to-microphysical conversion factors for lidars and ceilometers from extended AERONET data analyses: POLIPHON update A. Ansmann et al. https://doi.org/10.5194/amt-19-3801-2026
- Evidence of cloud sensitivity to above-cloud CCN as a function of environmental stability in the Southeast Atlantic based on remote sensing observations E. Lenhardt et al. https://doi.org/10.5194/acp-26-11709-2026
- Potential of polarization lidar to provide profiles of CCN- and INP-relevant aerosol parameters R. Mamouri & A. Ansmann https://doi.org/10.5194/acp-16-5905-2016
- A first global height-resolved cloud condensation nuclei data set derived from spaceborne lidar measurements G. Choudhury & M. Tesche https://doi.org/10.5194/essd-15-3747-2023
- Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks H. Andersen et al. https://doi.org/10.5194/acp-17-9535-2017
- Vertical profiles of cloud condensation nuclei number concentration and its empirical estimate from aerosol optical properties over the North China Plain R. Zhang et al. https://doi.org/10.5194/acp-22-14879-2022
- Statistical Evaluation of the Temperature Forecast Error in the Lower‐Level Troposphere on Short‐Range Timescales Induced by Aerosol Variability A. Yamagami et al. https://doi.org/10.1029/2022JD036595
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- Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic E. Lenhardt et al. https://doi.org/10.5194/amt-16-2037-2023
- Assessing Desert Dust Indirect Effects on Cloud Microphysics through a Cloud Nucleation Scheme: A Case Study over the Western Mediterranean K. Tsarpalis et al. https://doi.org/10.3390/rs12213473
- Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories J. Schmale et al. https://doi.org/10.5194/acp-18-2853-2018
- A Case Study in Low Aerosol Number Concentrations Over the Eastern North Atlantic: Implications for Pristine Conditions in the Remote Marine Boundary Layer S. Pennypacker & R. Wood https://doi.org/10.1002/2017JD027493
- Multi-campaign ship and aircraft observations of marine cloud condensation nuclei and droplet concentrations K. Sanchez et al. https://doi.org/10.1038/s41597-023-02372-z
- A new technique to retrieve aerosol vertical profiles using micropulse lidar and ground-based aerosol measurements B. Chen et al. https://doi.org/10.5194/amt-18-5841-2025
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- An observational study of the effects of aerosols on diurnal variation of heavy rainfall and associated clouds over Beijing–Tianjin–Hebei S. Zhou et al. https://doi.org/10.5194/acp-20-5211-2020
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- Limitations of passive remote sensing to constrain global cloud condensation nuclei P. Stier https://doi.org/10.5194/acp-16-6595-2016
- Impact of Cloud Condensation Nuclei Reduction on Cloud Characteristics and Solar Radiation during COVID-19 Lockdown 2020 in Moscow J. Shuvalova et al. https://doi.org/10.3390/atmos13101710
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- CCN Retrievals from Spaceborne Lidar Observations During ACEMED: Sensitivity to Smoke Parameterization A. Georgoulias et al. https://doi.org/10.3390/rs18040586
- Satellite‐Based Detection of Secondary Droplet Activation in Convective Clouds A. Efraim et al. https://doi.org/10.1029/2022JD036519
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- Distribution Characteristics of Aerosol Size and CCN during the Summer on Mt. Tian and Their Influencing Factors A. Liu et al. https://doi.org/10.3390/atmos11090912
- Derived Profiles of CCN and INP Number Concentrations in the Taklimakan Desert via Combined Polarization Lidar, Sun-Photometer, and Radiosonde Observations S. Zhang et al. https://doi.org/10.3390/rs15051216
- Estimation of cloud condensation nuclei number concentrations and comparison to in situ and lidar observations during the HOPE experiments C. Genz et al. https://doi.org/10.5194/acp-20-8787-2020
- Assessing the Challenges of Surface‐Level Aerosol Mass Estimates From Remote Sensing During the SEAC4RS and SEARCH Campaigns: Baseline Surface Observations and Remote Sensing in the Southeastern United States K. Kaku et al. https://doi.org/10.1029/2017JD028074
- Overview of the NOAA/ESRL Federated Aerosol Network E. Andrews et al. https://doi.org/10.1175/BAMS-D-17-0175.1
- Machine Learning Approach to Investigating the Relative Importance of Meteorological and Aerosol-Related Parameters in Determining Cloud Microphysical Properties F. Bender et al. https://doi.org/10.16993/tellusb.1868
- Estimating cloud condensation nuclei number concentrations using aerosol optical properties: role of particle number size distribution and parameterization Y. Shen et al. https://doi.org/10.5194/acp-19-15483-2019
- Dust mass, cloud condensation nuclei, and ice-nucleating particle profiling with polarization lidar: updated POLIPHON conversion factors from global AERONET analysis A. Ansmann et al. https://doi.org/10.5194/amt-12-4849-2019
- Estimating cloud condensation nuclei concentrations from CALIPSO lidar measurements G. Choudhury & M. Tesche https://doi.org/10.5194/amt-15-639-2022
- Retrieval of Cloud Condensation Nuclei Number Concentration Profiles From Lidar Extinction and Backscatter Data M. Lv et al. https://doi.org/10.1029/2017JD028102
- Satellite Retrieval of Cloud Condensation Nuclei Concentrations in Marine Stratocumulus by Using Clouds as CCN Chambers A. Efraim et al. https://doi.org/10.1029/2020JD032409
- A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations P. Patel et al. https://doi.org/10.5194/acp-24-2861-2024
- The dual-field-of-view polarization lidar technique: a new concept in monitoring aerosol effects in liquid-water clouds – theoretical framework C. Jimenez et al. https://doi.org/10.5194/acp-20-15247-2020
- Lidar estimates of birch pollen number, mass, and CCN-related concentrations M. Filioglou et al. https://doi.org/10.5194/acp-25-1639-2025
- Cloud condensation nuclei concentrations derived from the CAMS reanalysis K. Block et al. https://doi.org/10.5194/essd-16-443-2024
- Predicting cloud condensation nuclei number concentration based on conventional measurements of aerosol properties in the North China Plain Y. Zhang et al. https://doi.org/10.1016/j.scitotenv.2020.137473
- Pristine oceans are a significant source of uncertainty in quantifying global cloud condensation nuclei G. Choudhury et al. https://doi.org/10.5194/acp-25-3841-2025
- Cloud condensation nuclei phenomenology: predictions based on aerosol chemical and optical properties I. Zabala et al. https://doi.org/10.5194/acp-26-3697-2026
- Constraining the instantaneous aerosol influence on cloud albedo E. Gryspeerdt et al. https://doi.org/10.1073/pnas.1617765114
- Aerosol effective radius governs the relationship between cloud condensation nuclei (CCN) concentration and aerosol backscatter E. Lenhardt et al. https://doi.org/10.5194/acp-25-13747-2025
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