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| Titel |
Droplet number uncertainties associated with CCN: an assessment using observations and a global model adjoint |
| VerfasserIn |
R. H. Moore, V. A. Karydis, S. L. Capps, T. L. Lathem, A. Nenes |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 13, no. 8 ; Nr. 13, no. 8 (2013-04-24), S.4235-4251 |
| Datensatznummer |
250018604
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| Publikation (Nr.) |
 copernicus.org/acp-13-4235-2013.pdf |
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| Zusammenfassung |
| We use the Global Modelling Initiative (GMI) chemical transport model with a
cloud droplet parameterisation adjoint to quantify the sensitivity of cloud
droplet number concentration to uncertainties in predicting CCN
concentrations. Published CCN closure uncertainties for six different sets of
simplifying compositional and mixing state assumptions are used as proxies
for modelled CCN uncertainty arising from application of those scenarios. It
is found that cloud droplet number concentrations (Nd) are fairly
insensitive to the number concentration (Na) of aerosol which act as CCN
over the continents (∂lnNd/∂lnNa ~10–30%),
but the sensitivities exceed 70% in pristine regions such as the Alaskan
Arctic and remote oceans. This means that CCN concentration uncertainties of
4–71% translate into only 1–23% uncertainty in cloud droplet number, on
average. Since most of the anthropogenic indirect forcing is concentrated
over the continents, this work shows that the application of Köhler
theory and attendant simplifying assumptions in models is not a major source
of uncertainty in predicting cloud droplet number or anthropogenic aerosol
indirect forcing for the liquid, stratiform clouds simulated in these models.
However, it does highlight the sensitivity of some remote areas to pollution
brought into the region via long-range transport (e.g., biomass burning) or
from seasonal biogenic sources (e.g., phytoplankton as a source of
dimethylsulfide in the southern oceans). Since these transient processes are
not captured well by the climatological emissions inventories employed by
current large-scale models, the uncertainties in aerosol-cloud interactions
during these events could be much larger than those uncovered here. This finding
motivates additional measurements in these pristine regions, for which few observations
exist, to quantify the impact (and associated uncertainty) of transient aerosol processes on cloud properties. |
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