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  • Elsevier  (2)
  • Meteorologisches Institut der Albert-Ludwigs-Universität Freiburg  (1)
  • AGU (American geophysical union)
  • 2010-2014  (3)
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  • 1
    Publication Date: 2019-09-23
    Description: Highlights: • Phase II of the Coordinated Ocean-ice Reference Experiments (CORE-II) is introduced. • Solutions from CORE-II simulations from eighteen participating models are presented. • Mean states in the North Atlantic with a focus on AMOC are examined. • The North Atlantic solutions differ substantially among the models. • Many factors, including parameterization choices, contribute to these differences. Simulation characteristics from eighteen global ocean–sea-ice coupled models are presented with a focus on the mean Atlantic meridional overturning circulation (AMOC) and other related fields in the North Atlantic. These experiments use inter-annually varying atmospheric forcing data sets for the 60-year period from 1948 to 2007 and are performed as contributions to the second phase of the Coordinated Ocean-ice Reference Experiments (CORE-II). The protocol for conducting such CORE-II experiments is summarized. Despite using the same atmospheric forcing, the solutions show significant differences. As most models also differ from available observations, biases in the Labrador Sea region in upper-ocean potential temperature and salinity distributions, mixed layer depths, and sea-ice cover are identified as contributors to differences in AMOC. These differences in the solutions do not suggest an obvious grouping of the models based on their ocean model lineage, their vertical coordinate representations, or surface salinity restoring strengths. Thus, the solution differences among the models are attributed primarily to use of different subgrid scale parameterizations and parameter choices as well as to differences in vertical and horizontal grid resolutions in the ocean models. Use of a wide variety of sea-ice models with diverse snow and sea-ice albedo treatments also contributes to these differences. Based on the diagnostics considered, the majority of the models appear suitable for use in studies involving the North Atlantic, but some models require dedicated development effort.
    Type: Article , PeerReviewed
    Format: text
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  • 2
    Publication Date: 2019-09-23
    Description: Highlights: • Global mean sea level simulated in interannual CORE simulations. • Regional sea level patterns simulated in interannual CORE simulations. • Theoretical foundation for analysis of global mean sea level and regional patterns. Abstract: We provide an assessment of sea level simulated in a suite of global ocean-sea ice models using the interannual CORE atmospheric state to determine surface ocean boundary buoyancy and momentum fluxes. These CORE-II simulations are compared amongst themselves as well as to observation-based estimates. We focus on the final 15 years of the simulations (1993–2007), as this is a period where the CORE-II atmospheric state is well sampled, and it allows us to compare sea level related fields to both satellite and in situ analyses. The ensemble mean of the CORE-II simulations broadly agree with various global and regional observation-based analyses during this period, though with the global mean thermosteric sea level rise biased low relative to observation-based analyses. The simulations reveal a positive trend in dynamic sea level in the west Pacific and negative trend in the east, with this trend arising from wind shifts and regional changes in upper 700 m ocean heat content. The models also exhibit a thermosteric sea level rise in the subpolar North Atlantic associated with a transition around 1995/1996 of the North Atlantic Oscillation to its negative phase, and the advection of warm subtropical waters into the subpolar gyre. Sea level trends are predominantly associated with steric trends, with thermosteric effects generally far larger than halosteric effects, except in the Arctic and North Atlantic. There is a general anti-correlation between thermosteric and halosteric effects for much of the World Ocean, associated with density compensated changes.
    Type: Article , PeerReviewed , info:eu-repo/semantics/article
    Format: text
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  • 3
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    Meteorologisches Institut der Albert-Ludwigs-Universität Freiburg
    In:  EPIC39. Deutsche Klimatagung, Freiburg, Germany, 2012-10-09-2012-10-12Freiburg, Germany, Meteorologisches Institut der Albert-Ludwigs-Universität Freiburg
    Publication Date: 2019-07-17
    Description: Das Finite Element Sea ice Ocean Model FESOM ist mit dem atmosphärischen Zirkulationsmodell ECHAM gekoppelt worden. Durch das unstrukturierte Gitter des Ozeanmodells ist es möglich, das Gitter des Ozeanmodells sehr variabel zu gestalten, um Schlüsselregionen oder Regionen von besonderem Interesse in hoher Auflösung zu simulieren, während andere Regionen niedriger aufgelöst bleiben. In unseren Sensitivitätsstudien nutzen wir verschieden hohe Auflösungen in der Arktis und in den nördlichen mittleren Breiten. Kombiniert mit variierten Modellparametern in der Atmosphäre und im Ozean wie z.B. Treibhausgaskonzentrationen, Schwerewellenwiderstand und Meereisalbedo erreicht das gekoppelte System zwei unterschiedliche Zustände, einen mit stark ausgeprägter atlantischer meridionaler Umwälzzirkulation und deutlichem Irminger-Strom und einen mit schwach ausgeprägter atlantischer meridionaler Umwälzzirkulation und schwachem Irminger-Strom. Im ersten Zustand beträgt die Stärke der atlantischen meridionalen Umwälzzirkulation zwischen 20 und 25 Sverdrup während der zweite Zustand zeitweise nur zwischen 5 und 10 Sverdrup aufweist. Die Beobachtungen liegen mit durchschnittlich 18 Sverdrup dazwischen. Um physikalische Ursachen für diese Unterschiede feststellen zu können, werden verschiedene Zeitpunkte der Simulation mit stark ausgeprägter atlantischer meridionaler Umwälzzirkulation ausgewählt. Der Zustand des Ozeans und der Atmosphäre an diesen ausgewählten Zeitpunkten wird verwendet, um Modellsimulationen mit der Modellversion, mit der eine schwach ausgeprägte atlantische meridionale Umwälzzirkulation simuliert wird, zu initialisieren. Anschließend wird die mittlere Abweichung der auf diese Weise initialisierten Modellsimulationen von der Stammsimulation nach Tagen, Wochen, Monaten und Jahren analysiert, um festzustellen, in welchen Gebieten sich die ersten Unterschiede einstellen und wie sich diese ausbreiten. Dies wird anschließend wiederholt, indem in weiteren Simulationen sukzessive die einzelnen Unterschiede zwischen den Modellversionen zugeschaltet werden, um herauszufinden, welche Modelländerung den größten Einfluss hat.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
    Format: application/pdf
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