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Titel |
Cloud-scale model intercomparison of chemical constituent transport in deep convection |
VerfasserIn |
M. C. Barth, S.-W. Kim, C. Wang, K. E. Pickering, L. E. Ott, G. Stenchikov, M. Leriche, S. Cautenet, J.-P. Pinty, Ch. Barthe, C. Mari, J. H. Helsdon, R. D. Farley, A. M. Fridlind, A. S. Ackerman, V. Spiridonov, B. Telenta |
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 ; 7, no. 18 ; Nr. 7, no. 18 (2007-09-18), S.4709-4731 |
Datensatznummer |
250005193
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Publikation (Nr.) |
copernicus.org/acp-7-4709-2007.pdf |
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Zusammenfassung |
Transport and scavenging of chemical constituents in deep convection is
important to understanding the composition of the troposphere and therefore
chemistry-climate and air quality issues. High resolution cloud chemistry
models have been shown to represent convective processing of trace gases
quite well. To improve the representation of sub-grid convective transport
and wet deposition in large-scale models, general characteristics, such as
species mass flux, from the high resolution cloud chemistry models can be
used. However, it is important to understand how these models behave when
simulating the same storm. The intercomparison described here examines
transport of six species. CO and O3, which are primarily transported,
show good agreement among models and compare well with observations. Models
that included lightning production
of NOx reasonably predict NOx mixing ratios in the anvil compared
with observations, but the NOx variability is much larger than that
seen for CO and O3. Predicted anvil mixing ratios of the soluble
species, HNO3, H2O2, and CH2O, exhibit significant
differences among models, attributed to different schemes in these models of
cloud processing including the role of the ice phase, the impact of
cloud-modified photolysis rates on the chemistry, and the representation of
the species chemical reactivity. The lack of measurements of these species
in the convective outflow region does not allow us to evaluate the model
results with observations. |
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