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| Titel |
Near-surface meteorology during the Arctic Summer Cloud Ocean Study (ASCOS): evaluation of reanalyses and global climate models |
| VerfasserIn |
G. de Boer, M. D. Shupe, P. M. Caldwell, S. E. Bauer, O. Persson, J. S. Boyle, M. Kelley, S. A. Klein, M. Tjernström |
| 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 ; 14, no. 1 ; Nr. 14, no. 1 (2014-01-13), S.427-445 |
| Datensatznummer |
250118262
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| Publikation (Nr.) |
 copernicus.org/acp-14-427-2014.pdf |
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| Zusammenfassung |
| Atmospheric measurements from the Arctic Summer Cloud Ocean Study (ASCOS) are
used to evaluate the performance of three atmospheric reanalyses (European Centre for Medium Range Weather Forecasting (ECMWF)-Interim reanalysis, National Center
for Environmental Prediction (NCEP)-National Center for Atmospheric
Research (NCAR) reanalysis,
and NCEP-DOE (Department of Energy) reanalysis) and two global climate models (CAM5 (Community Atmosphere Model 5) and NASA GISS (Goddard Institute
for Space Studies) ModelE2) in
simulation of the high Arctic environment. Quantities analyzed include near
surface meteorological variables such as temperature, pressure, humidity and
winds, surface-based estimates of cloud and precipitation properties, the
surface energy budget, and lower atmospheric temperature structure. In
general, the models perform well in simulating large-scale dynamical
quantities such as pressure and winds. Near-surface temperature and lower
atmospheric stability, along with surface energy budget terms, are not as well
represented due largely to errors in simulation of cloud occurrence, phase
and altitude. Additionally, a development version of CAM5, which features
improved handling of cloud macro physics, has demonstrated to improve
simulation of cloud properties and liquid water amount. The ASCOS period
additionally provides an excellent example of the benefits gained by evaluating individual
budget terms, rather than simply evaluating the net end product, with large
compensating errors between individual surface energy budget terms that result
in the best net energy budget. |
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