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| Titel |
Interannual variability in hindcasts of atmospheric chemistry: the role of meteorology |
| VerfasserIn |
P. Hess, N. Mahowald |
| 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 ; 9, no. 14 ; Nr. 9, no. 14 (2009-07-29), S.5261-5280 |
| Datensatznummer |
250007541
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| Publikation (Nr.) |
 copernicus.org/acp-9-5261-2009.pdf |
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| Zusammenfassung |
| Two 40-year meteorological datasets are used to drive the Model of
Ozone and Related Tracers chemical transport model, version 2
(MOZART2) in hindcast simulations. One dataset is from the National
Center for Environmental Prediction/National Center for Atmospheric
Research (NCEP/NCAR) reanalysis, the second dataset uses
meteorology from the Community Atmosphere Model (CAM3) forced with
observed interannually varying sea surface temperatures. All
emissions, except those from lightning are annually constant. Analysis
of these simulations focuses on the period between 1979–1999, due to meteorological
discontinuities in the NCEP reanalysis during the 1970s. The
meteorology using CAM3 captures observed trends in temperature and water
vapor; the simulation using NCEP
meteorology does not. This paper examines the regional and global
interannual variability of various chemical and meteorological fields:
CO, OH, O3 and HNO3, the surface photolysis rate
of NO2 (as a proxy for overhead cloudiness), lightning NO
emissions, water vapor, planetary boundary layer height, and
temperature. The variability due to changes in emissions is not
considered in this analysis. In both the NCEP and CAM3 simulations the
relative variability of CO, OH, O3 and HNO3 are
qualitatively similar, with variability maxima both in the tropics and
the high latitudes. Locally, relative variability generally ranges
between 3 and 10%; globally the tropospheric variability generally
ranges from half to one percent, but can be higher. For most fields
the leading global Empirical Orthogonal Function explains approximately
10% of the variability and correlates significantly with El
Niño. In both simulations the first principal component of
a multiple tracer, globally averaged analysis shows a strong coupling
between surface temperature, measures of the hydrological cycle, CO
and OH, but is not correlated with El Niño. In both simulations we
examine the global response of the selected variables to changes in
global surface temperature, and compare with a climate simulation over
the 21st century. |
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