A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations
Abstract N CCN) using aerosol optical properties measured by a multiwavelength lidar. The algorithm considers five distinct aerosol subtypes with bimodal size distributions. The inversion used the lookup tables developed in this study, based on the observations from the Aerosol Robotic Network, to efficiently retrieve optimal particle size distributions from lidar measurements. The method derives dry aerosol optical properties by implementing hygroscopic enhancement factors in lidar measurements. The retrieved optically equivalent particle size distributions and aerosol-type-dependent particle composition are utilized to calculate critical diameters using κ N CCN N CCN N CCN N CCN has been retrieved for the first time using a proposed algorithm from spaceborne lidar – Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) – measurements. The application of this new capability demonstrates the potential for constructing a 3D CCN climatology at a global scale, which helps to better quantify ACI effects and thus reduce the uncertainty in aerosol climate forcing.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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A remote sensing algorithm for vertically resolved cloud condensation nuclei number concentrations from airborne and spaceborne lidar observations ; volume:24 ; number:5 ; year:2024 ; pages:2861-2883 ; extent:23
Atmospheric chemistry and physics ; 24, Heft 5 (2024), 2861-2883 (gesamt 23)
- Creator
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Patel, Piyushkumar N.
Jiang, Jonathan H.
Gautam, Ritesh
Gadhavi, Harish
Kalashnikova, Olga
Garay, Michael J.
Gao, Lan
Xu, Feng
Omar, Ali
- DOI
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10.5194/acp-24-2861-2024
- URN
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urn:nbn:de:101:1-2024030703154533494345
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 11:02 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Patel, Piyushkumar N.
- Jiang, Jonathan H.
- Gautam, Ritesh
- Gadhavi, Harish
- Kalashnikova, Olga
- Garay, Michael J.
- Gao, Lan
- Xu, Feng
- Omar, Ali