Articles | Volume 15, issue 3
https://doi.org/10.5194/amt-15-639-2022
© Author(s) 2022. 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-15-639-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Feb 2022
Research article |
| 08 Feb 2022
| 08 Feb 2022
Estimating cloud condensation nuclei concentrations from CALIPSO lidar measurements
Goutam Choudhury
CORRESPONDING AUTHOR
Leipzig Institute for Meteorology (LIM), Leipzig University, Stephanstrasse 3, 04103 Leipzig, Germany
Matthias Tesche
Leipzig Institute for Meteorology (LIM), Leipzig University, Stephanstrasse 3, 04103 Leipzig, Germany
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Cited
18 citations as recorded by crossref.
- Retrieval and validation of cloud condensation nuclei from satellite and airborne measurements over the Indian Monsoon region A. Aravindhavel et al. 10.1016/j.atmosres.2023.106802
- Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations S. Tang et al. 10.5194/gmd-16-6355-2023
- POLIPHON conversion factors for retrieving dust-related cloud condensation nuclei and ice-nucleating particle concentration profiles at oceanic sites Y. He et al. 10.5194/amt-16-1951-2023
- A machine learning paradigm for necessary observations to reduce uncertainties in aerosol climate forcing J. Redemann & L. Gao 10.1038/s41467-024-52747-y
- 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
- A Regional Aerosol Model for the Middle Urals Based on CALIPSO Measurements E. Nagovitsyna et al. 10.3390/atmos15010048
- Cloud condensation nuclei concentrations derived from the CAMS reanalysis K. Block et al. 10.5194/essd-16-443-2024
- Cloud Characteristics in South China Using Ka-Band Millimeter Cloud Radar Datasets H. Li et al. 10.3390/atmos15040486
- Analysis of the relationship between dust aerosol and precipitation in spring over East Asia using EOF and SVD methods H. Liu et al. 10.1016/j.scitotenv.2023.168437
- Frontiers in Satellite‐Based Estimates of Cloud‐Mediated Aerosol Forcing D. Rosenfeld et al. 10.1029/2022RG000799
- A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations F. Alexandri et al. 10.5194/amt-17-1739-2024
- Evaluation of aerosol number concentrations from CALIPSO with ATom airborne in situ measurements G. Choudhury et al. 10.5194/acp-22-7143-2022
- Developing a climatological simplification of aerosols to enter the cloud microphysics of a global climate model U. Proske et al. 10.5194/acp-24-5907-2024
- A first global height-resolved cloud condensation nuclei data set derived from spaceborne lidar measurements G. Choudhury & M. Tesche 10.5194/essd-15-3747-2023
- Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic E. Lenhardt et al. 10.5194/amt-16-2037-2023
- Assessment of CALIOP-Derived CCN Concentrations by In Situ Surface Measurements G. Choudhury & M. Tesche 10.3390/rs14143342
- 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. 10.5194/acp-22-14879-2022
- Impact of Adaptively Thinned GOES-16 Cloud Water Path in an Ensemble Data Assimilation System S. Mallick 10.3390/meteorology1040032
18 citations as recorded by crossref.
- Retrieval and validation of cloud condensation nuclei from satellite and airborne measurements over the Indian Monsoon region A. Aravindhavel et al. 10.1016/j.atmosres.2023.106802
- Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations S. Tang et al. 10.5194/gmd-16-6355-2023
- POLIPHON conversion factors for retrieving dust-related cloud condensation nuclei and ice-nucleating particle concentration profiles at oceanic sites Y. He et al. 10.5194/amt-16-1951-2023
- A machine learning paradigm for necessary observations to reduce uncertainties in aerosol climate forcing J. Redemann & L. Gao 10.1038/s41467-024-52747-y
- 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
- A Regional Aerosol Model for the Middle Urals Based on CALIPSO Measurements E. Nagovitsyna et al. 10.3390/atmos15010048
- Cloud condensation nuclei concentrations derived from the CAMS reanalysis K. Block et al. 10.5194/essd-16-443-2024
- Cloud Characteristics in South China Using Ka-Band Millimeter Cloud Radar Datasets H. Li et al. 10.3390/atmos15040486
- Analysis of the relationship between dust aerosol and precipitation in spring over East Asia using EOF and SVD methods H. Liu et al. 10.1016/j.scitotenv.2023.168437
- Frontiers in Satellite‐Based Estimates of Cloud‐Mediated Aerosol Forcing D. Rosenfeld et al. 10.1029/2022RG000799
- A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations F. Alexandri et al. 10.5194/amt-17-1739-2024
- Evaluation of aerosol number concentrations from CALIPSO with ATom airborne in situ measurements G. Choudhury et al. 10.5194/acp-22-7143-2022
- Developing a climatological simplification of aerosols to enter the cloud microphysics of a global climate model U. Proske et al. 10.5194/acp-24-5907-2024
- A first global height-resolved cloud condensation nuclei data set derived from spaceborne lidar measurements G. Choudhury & M. Tesche 10.5194/essd-15-3747-2023
- Use of lidar aerosol extinction and backscatter coefficients to estimate cloud condensation nuclei (CCN) concentrations in the southeast Atlantic E. Lenhardt et al. 10.5194/amt-16-2037-2023
- Assessment of CALIOP-Derived CCN Concentrations by In Situ Surface Measurements G. Choudhury & M. Tesche 10.3390/rs14143342
- 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. 10.5194/acp-22-14879-2022
- Impact of Adaptively Thinned GOES-16 Cloud Water Path in an Ensemble Data Assimilation System S. Mallick 10.3390/meteorology1040032
Latest update: 23 Nov 2024
Short summary
Aerosols are tiny particles suspended in the atmosphere. A fraction of these particles can form clouds and are called cloud condensation nuclei (CCN). Measurements of such aerosol particles are necessary to study the aerosol–cloud interactions and reduce the uncertainty in our future climate predictions. We present a novel methodology to estimate global 3D CCN concentrations from the CALIPSO satellite measurements. The final data set will be used to study the aerosol–cloud interactions.
Aerosols are tiny particles suspended in the atmosphere. A fraction of these particles can form...
