Climate Dynamics

, Volume 21, Issue 1, pp 27–51 | Cite as

Description and evaluation of the bergen climate model: ARPEGE coupled with MICOM

  • T. FurevikEmail author
  • M. Bentsen
  • H. Drange
  • I. K. T. Kindem
  • N. G. Kvamstø
  • A. Sorteberg


A new coupled atmosphere–ocean–sea ice model has been developed, named the Bergen Climate Model (BCM). It consists of the atmospheric model ARPEGE/IFS, together with a global version of the ocean model MICOM including a dynamic–thermodynamic sea ice model. The coupling between the two models uses the OASIS software package. The new model concept is described, and results from a 300-year control integration is evaluated against observational data. In BCM, both the atmosphere and the ocean components use grids which can be irregular and have non-matching coastlines. Much effort has been put into the development of optimal interpolation schemes between the models, in particular the non-trivial problem of flux conservation in the coastal areas. A flux adjustment technique has been applied to the heat and fresh-water fluxes. There is, however, a weak drift in global mean sea-surface temperature (SST) and sea-surface salinity (SSS) of respectively 0.1 °C and 0.02 psu per century. The model gives a realistic simulation of the radiation balance at the top-of-the-atmosphere, and the net surface fluxes of longwave, shortwave, and turbulent heat fluxes are within observed values. Both global and total zonal means of cloud cover and precipitation are fairly close to observations, and errors are mainly related to the strength and positioning of the Hadley cell. The mean sea-level pressure (SLP) is well simulated, and both the mean state and the interannual standard deviation show realistic features. The SST field is several degrees too cold in the equatorial upwelling area in the Pacific, and about 1 °C too warm along the eastern margins of the oceans, and in the polar regions. The deviation from Levitus salinity is typically 0.1 psu – 0.4 psu, with a tendency for positive anomalies in the Northern Hemisphere, and negative in the Southern Hemisphere. The sea-ice distribution is realistic, but with too thin ice in the Arctic Ocean and too small ice coverage in the Southern Ocean. These model deficiencies have a strong influence on the surface air temperatures in these regions. Horizontal oceanic mass transports are in the lower range of those observed. The strength of the meridional overturning in the Atlantic is 18 Sv. An analysis of the large-scale variability in the model climate reveals realistic El Niño – Southern Oscillation (ENSO) and North Atlantic–Arctic Oscillation (NAO/AO) characteristics in the SLP and surface temperatures, including spatial patterns, frequencies, and strength. While the NAO/AO spectrum is white in SLP and red in temperature, the ENSO spectrum shows an energy maximum near 3 years.


Outgoing Longwave Radiation Freshwater Flux Hadley Cell NCEP Reanalysis Flux Adjustment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The authors are grateful to Laurent Terray at CERFACS, Toulouse, for the initial set-up of the OASIS coupler in Bergen, to Michel Déqué and David Salas Mélia, Meteo-France, Toulouse, for providing technical assistance and support, and to Lennart Bengtsson, MPI, Hamburg, for a series of useful discussions and thorough guidance during the work. Constructive criticisms and suggestions made by Ronald J. Stouffer, GFDL, Princeton, during the review process, are greatly appreciated. The development of the Bergen Climate Model and the model integrations have received support from the Research Council of Norway through the RegClim project, the "Spissforskningsmidler" (MB), and the Programme for Supercomputing. Additional funding has been received from the Board of Marine Sciences, University of Bergen, and the European Commission funded project PREDICATE (EVK2-CT-1999-00020) (HD). This is contribution A0013 from the Bjerknes Centre for Climate Research.


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Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  • T. Furevik
    • 1
    • 2
    Email author
  • M. Bentsen
    • 1
    • 3
  • H. Drange
    • 1
    • 2
    • 3
  • I. K. T. Kindem
    • 2
    • 3
  • N. G. Kvamstø
    • 2
  • A. Sorteberg
    • 2
    • 3
  1. 1.Nansen Environmental and Remote Sensing Center, Bergen, Norway
  2. 2.Geophysical Institute, University of Bergen, Allégaten 70, 5007 Bergen, Norway
  3. 3.Bjerknes Centre for Climate Research, Bergen, Norway

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