Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations
Large cloud condensation nuclei (CCN) (e.g., aged dust particles and seasalt) cannot attain their equilibrium size during the typical timescale of cloud droplet activation. Cloud activation parameterizations applied to aerosol with a large fraction of large CCN often do not account for this limitati...
| Main Authors: | , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2010
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| _version_ | 1797053306708688896 |
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| author | Barahona, D West, R Stier, P Romakkaniemi, S Kokkola, H Nenes, A |
| author_facet | Barahona, D West, R Stier, P Romakkaniemi, S Kokkola, H Nenes, A |
| author_sort | Barahona, D |
| collection | OXFORD |
| description | Large cloud condensation nuclei (CCN) (e.g., aged dust particles and seasalt) cannot attain their equilibrium size during the typical timescale of cloud droplet activation. Cloud activation parameterizations applied to aerosol with a large fraction of large CCN often do not account for this limitation adequately and can give biased predictions of cloud droplet number concentration (CDNC). Here we present a simple approach to address this problem that can easily be incorporated into cloud activation parameterizations. This method is demonstrated with activation parameterizations based on the "population splitting" concept of Nenes and Seinfeld (2003); it is shown that accounting for large CCN effects eliminates a positive bias in CDNC where the aerosol dry geometric diameter is greater than 0.5 andmu;m. The method proposed here can also be extended to include the water vapor depletion from pre-existing droplets and ice crystals in global and regional atmospheric models. |
| first_indexed | 2024-03-06T18:42:00Z |
| format | Journal article |
| id | oxford-uuid:0d2df454-ac5f-4910-8fff-5b0c746ff538 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T18:42:00Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | oxford-uuid:0d2df454-ac5f-4910-8fff-5b0c746ff5382022-03-26T09:39:12ZComprehensively accounting for the effect of giant CCN in cloud activation parameterizationsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:0d2df454-ac5f-4910-8fff-5b0c746ff538EnglishSymplectic Elements at Oxford2010Barahona, DWest, RStier, PRomakkaniemi, SKokkola, HNenes, ALarge cloud condensation nuclei (CCN) (e.g., aged dust particles and seasalt) cannot attain their equilibrium size during the typical timescale of cloud droplet activation. Cloud activation parameterizations applied to aerosol with a large fraction of large CCN often do not account for this limitation adequately and can give biased predictions of cloud droplet number concentration (CDNC). Here we present a simple approach to address this problem that can easily be incorporated into cloud activation parameterizations. This method is demonstrated with activation parameterizations based on the "population splitting" concept of Nenes and Seinfeld (2003); it is shown that accounting for large CCN effects eliminates a positive bias in CDNC where the aerosol dry geometric diameter is greater than 0.5 andmu;m. The method proposed here can also be extended to include the water vapor depletion from pre-existing droplets and ice crystals in global and regional atmospheric models. |
| spellingShingle | Barahona, D West, R Stier, P Romakkaniemi, S Kokkola, H Nenes, A Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations |
| title | Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations |
| title_full | Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations |
| title_fullStr | Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations |
| title_full_unstemmed | Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations |
| title_short | Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations |
| title_sort | comprehensively accounting for the effect of giant ccn in cloud activation parameterizations |
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