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| Titel |
The cloud–aerosol–radiation (CAR) ensemble modeling system |
| VerfasserIn |
X.-Z. Liang, F. Zhang |
| 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. 16 ; Nr. 13, no. 16 (2013-08-22), S.8335-8364 |
| Datensatznummer |
250085645
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| Publikation (Nr.) |
 copernicus.org/acp-13-8335-2013.pdf |
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| Zusammenfassung |
| A cloud–aerosol–radiation (CAR) ensemble modeling system has been developed
to incorporate the largest choices of alternate parameterizations for cloud
properties (cover, water, radius, optics, geometry), aerosol properties
(type, profile, optics), radiation transfers (solar, infrared), and their
interactions. These schemes form the most comprehensive collection currently
available in the literature, including those used by the world's leading
general circulation models (GCMs). CAR provides a unique framework to
determine (via intercomparison across all schemes), reduce (via optimized
ensemble simulations), and attribute specific key factors for (via physical
process sensitivity analyses) the model discrepancies and uncertainties in
representing greenhouse gas, aerosol, and cloud radiative forcing effects.
This study presents a general description of the CAR system and illustrates
its capabilities for climate modeling applications, especially in the
context of estimating climate sensitivity and uncertainty range caused by
cloud–aerosol–radiation interactions. For demonstration purposes, the
evaluation is based on several CAR standalone and coupled climate model
experiments, each comparing a limited subset of the full system ensemble
with up to 896 members. It is shown that the quantification of radiative
forcings and climate impacts strongly depends on the choices of the cloud,
aerosol, and radiation schemes. The prevailing schemes used in current GCMs
are likely insufficient in variety and physically biased in a significant
way. There exists large room for improvement by optimally combining
radiation transfer with cloud property schemes. |
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