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| Titel |
On the representation of immersion and condensation freezing in cloud models using different nucleation schemes |
| VerfasserIn |
B. Ervens, G. Feingold |
| 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 ; 12, no. 13 ; Nr. 12, no. 13 (2012-07-06), S.5807-5826 |
| Datensatznummer |
250011300
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| Publikation (Nr.) |
 copernicus.org/acp-12-5807-2012.pdf |
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| Zusammenfassung |
Ice nucleation in clouds is often observed at temperatures >235 K,
pointing to heterogeneous freezing as a predominant mechanism. Many models
deterministically predict the number concentration of ice particles as a
function of temperature and/or supersaturation. Several laboratory
experiments, at constant temperature and/or supersaturation, report
heterogeneous freezing as a stochastic, time-dependent process that follows
classical nucleation theory; this might appear to contradict deterministic
models that predict singular freezing behavior.
We explore the extent to which the choice of nucleation scheme
(deterministic/stochastic, single/multiple contact angles θ) affects the
prediction of the fraction of frozen ice nuclei (IN) and cloud evolution for
a predetermined maximum IN concentration. A box model with constant
temperature and supersaturation is used to mimic published laboratory
experiments of immersion freezing of monodisperse (800 nm) kaolinite
particles (~243 K), and the fitness of different nucleation schemes.
Sensitivity studies show that agreement of all five schemes is restricted to
the narrow parameter range (time, temperature, IN diameter) in the original
laboratory studies, and that model results diverge for a wider range of
conditions.
The schemes are implemented in an adiabatic parcel model that includes
feedbacks of the formation and growth of drops and ice particles on
supersaturation during ascent. Model results for the monodisperse IN
population (800 nm) show that these feedbacks limit ice nucleation events,
often leading to smaller differences in number concentration of ice
particles and ice water content (IWC) between stochastic and deterministic
approaches than expected from the box model studies. However, because the
different parameterizations of θ distributions and time-dependencies
are highly sensitive to IN size, simulations using polydisperse IN result in
great differences in predicted ice number concentrations and IWC between the
different schemes. The differences in IWC are mostly due to the different
temperatures of the onset of freezing in the nucleation schemes that affect
the temporal evolution of the ice number concentration. The growth rates of
ice particles are not affected by the choice of the nucleation scheme, which
leads to very similar particle sizes. Finally, since the choice of
nucleation scheme determines the temperature range over which ice nucleation
occurs, at habit-prone temperatures (~253 K), there is the potential
for variability in the initial inherent growth ratio of ice particles, which
can cause amplification or reduction in differences in predicted IWC. |
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