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Titel |
The Arctic summer atmosphere: an evaluation of reanalyses using ASCOS data |
VerfasserIn |
C. Wesslén, M. Tjernström, D. H. Bromwich, G. de Boer, A. M. L. Ekman, L.-S. Bai, S.-H. Wang |
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. 5 ; Nr. 14, no. 5 (2014-03-14), S.2605-2624 |
Datensatznummer |
250118480
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Publikation (Nr.) |
copernicus.org/acp-14-2605-2014.pdf |
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Zusammenfassung |
The Arctic has experienced large climate changes over recent decades, the
largest for any region on Earth. To understand the underlying reasons for
this climate sensitivity, reanalysis is an invaluable tool. The Arctic
System Reanalysis (ASR) is a regional reanalysis, forced by ERA-Interim at
the lateral boundaries and incorporating model physics adapted to Arctic
conditions, developed to serve as a state-of-the-art, high-resolution
synthesis tool for assessing Arctic climate variability and monitoring
Arctic climate change.
We use data from Arctic Summer Cloud-Ocean Study (ASCOS) to evaluate the
performance of ASR and ERA-Interim for the Arctic Ocean. The ASCOS field
experiment was deployed on the Swedish icebreaker Oden north of
87° N in the Atlantic sector of the Arctic during August and early
September 2008. Data were collected during the transits from and to
Longyearbyen and the 3-week ice drift with Oden moored to a drifting
multiyear ice floe. These data are independent and detailed enough to
evaluate process descriptions.
The reanalyses captures basic meteorological variations coupled to the
synoptic-scale systems, but have difficulties in estimating clouds and
atmospheric moisture. While ERA-Interim has a systematic warm bias in the
lowest troposphere, ASR has a cold bias of about the same magnitude on
average. The results also indicate that more sophisticated descriptions of
cloud microphysics in ASR did not significantly improve the modeling of
cloud properties compared to ERA-Interim. This has consequences for the
radiation balance, and hence the surface temperature, and illustrate how a
modeling problem in one aspect of the atmosphere, here the clouds, feeds
back to other parameters, especially near the surface and in the boundary
layer. |
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