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| Titel |
Quantitative assessment of Southern Hemisphere ozone in chemistry-climate model simulations |
| VerfasserIn |
A. Yu. Karpechko, N. P. Gillett, B. Hassler, K. H. Rosenlof, E. Rozanov |
| 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 ; 10, no. 3 ; Nr. 10, no. 3 (2010-02-08), S.1385-1400 |
| Datensatznummer |
250008050
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| Publikation (Nr.) |
 copernicus.org/acp-10-1385-2010.pdf |
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| Zusammenfassung |
| Stratospheric ozone recovery in the Southern Hemisphere is expected to drive
pronounced trends in atmospheric temperature and circulation from the
stratosphere to the troposphere in the 21st century; therefore ozone
changes need to be accounted for in future climate simulations. Many climate
models do not have interactive ozone chemistry and rely on prescribed ozone
fields, which may be obtained from coupled chemistry-climate model (CCM)
simulations. However CCMs vary widely in their predictions of ozone
evolution, complicating the selection of ozone boundary conditions for
future climate simulations. In order to assess which models might be
expected to better simulate future ozone evolution, and thus provide more
realistic ozone boundary conditions, we assess the ability of twelve CCMs to
simulate observed ozone climatology and trends and rank the models according
to their errors averaged across the individual diagnostics chosen. According
to our analysis no one model performs better than the others in all the
diagnostics; however, combining errors in individual diagnostics into one
metric of model performance allows us to objectively rank the models. The
multi-model average shows better overall agreement with the observations
than any individual model. Based on this analysis we conclude that the
multi-model average ozone projection presents the best estimate of future
ozone evolution and recommend it for use as a boundary condition in future
climate simulations. Our results also demonstrate a sensitivity of the
analysis to the choice of reference data set for vertical ozone distribution
over the Antarctic, highlighting the constraints that large observational
uncertainty imposes on such model verification. |
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