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  • 16. Hazeleger, W.
    et al.
    Wang, X.
    Severijns, C.
    Stefanescu, S.
    Bintanja, R.
    Sterl, A.
    Wyser, Klaus
    SMHI, Research Department, Climate research - Rossby Centre.
    Semmler, T.
    Yang, S.
    van den Hurk, B.
    van Noije, T.
    van der Linden, E.
    van der Wiel, K.
    EC-Earth V2.2: description and validation of a new seamless earth system prediction model2012In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 39, no 11, p. 2611-2629Article in journal (Refereed)
    Abstract [en]

    EC-Earth, a new Earth system model based on the operational seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (ECMWF), is presented. The performance of version 2.2 (V2.2) of the model is compared to observations, reanalysis data and other coupled atmosphere-ocean-sea ice models. The large-scale physical characteristics of the atmosphere, ocean and sea ice are well simulated. When compared to other coupled models with similar complexity, the model performs well in simulating tropospheric fields and dynamic variables, and performs less in simulating surface temperature and fluxes. The surface temperatures are too cold, with the exception of the Southern Ocean region and parts of the Northern Hemisphere extratropics. The main patterns of interannual climate variability are well represented. Experiments with enhanced CO2 concentrations show well-known responses of Arctic amplification, land-sea contrasts, tropospheric warming and stratospheric cooling. The global climate sensitivity of the current version of EC-Earth is slightly less than 1 K/(W m(-2)). An intensification of the hydrological cycle is found and strong regional changes in precipitation, affecting monsoon characteristics. The results show that a coupled model based on an operational seasonal prediction system can be used for climate studies, supporting emerging seamless prediction strategies.

  • 17.
    Koenigk, Torben
    et al.
    SMHI, Research Department, Climate research - Rossby Centre.
    Beatty, Christof Konig
    Caian, Mihaela
    SMHI, Research Department, Climate research - Rossby Centre.
    Doescher, Ralf
    SMHI, Research Department, Climate research - Rossby Centre.
    Wyser, Klaus
    SMHI, Research Department, Climate research - Rossby Centre.
    Potential decadal predictability and its sensitivity to sea ice albedo parameterization in a global coupled model2012In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 38, no 11-12, p. 2389-2408Article in journal (Refereed)
    Abstract [en]

    Decadal prediction is one focus of the upcoming 5th IPCC Assessment report. To be able to interpret the results and to further improve the decadal predictions it is important to investigate the potential predictability in the participating climate models. This study analyzes the upper limit of climate predictability on decadal time scales and its dependency on sea ice albedo parameterization by performing two perfect ensemble experiments with the global coupled climate model EC-Earth. In the first experiment, the standard albedo formulation of EC-Earth is used, in the second experiment sea ice albedo is reduced. The potential prognostic predictability is analyzed for a set of oceanic and atmospheric parameters. The decadal predictability of the atmospheric circulation is small. The highest potential predictability was found in air temperature at 2 m height over the northern North Atlantic and the southern South Atlantic. Over land, only a few areas are significantly predictable. The predictability for continental size averages of air temperature is relatively good in all northern hemisphere regions. Sea ice thickness is highly predictable along the ice edges in the North Atlantic Arctic Sector. The meridional overturning circulation is highly predictable in both experiments and governs most of the decadal climate predictability in the northern hemisphere. The experiments using reduced sea ice albedo show some important differences like a generally higher predictability of atmospheric variables in the Arctic or higher predictability of air temperature in Europe. Furthermore, decadal variations are substantially smaller in the simulations with reduced ice albedo, which can be explained by reduced sea ice thickness in these simulations.

  • 18. Sterl, Andreas
    et al.
    Bintanja, Richard
    Brodeau, Laurent
    Gleeson, Emily
    Koenigk, Torben
    SMHI, Research Department, Climate research - Rossby Centre.
    Schmith, Torben
    Semmler, Tido
    Severijns, Camiel
    Wyser, Klaus
    SMHI, Research Department, Climate research - Rossby Centre.
    Yang, Shuting
    A look at the ocean in the EC-Earth climate model2012In: Climate Dynamics, ISSN 0930-7575, E-ISSN 1432-0894, Vol. 39, no 11, p. 2631-2657Article in journal (Refereed)
    Abstract [en]

    EC-Earth is a newly developed global climate system model. Its core components are the Integrated Forecast System (IFS) of the European Centre for Medium Range Weather Forecasts (ECMWF) as the atmosphere component and the Nucleus for European Modelling of the Ocean (NEMO) developed by Institute Pierre Simon Laplace (IPSL) as the ocean component. Both components are used with a horizontal resolution of roughly one degree. In this paper we describe the performance of NEMO in the coupled system by comparing model output with ocean observations. We concentrate on the surface ocean and mass transports. It appears that in general the model has a cold and fresh bias, but a much too warm Southern Ocean. While sea ice concentration and extent have realistic values, the ice tends to be too thick along the Siberian coast. Transports through important straits have realistic values, but generally are at the lower end of the range of observational estimates. Exceptions are very narrow straits (Gibraltar, Bering) which are too wide due to the limited resolution. Consequently the modelled transports through them are too high. The strength of the Atlantic meridional overturning circulation is also at the lower end of observational estimates. The interannual variability of key variables and correlations between them are realistic in size and pattern. This is especially true for the variability of surface temperature in the tropical Pacific (El Nio). Overall the ocean component of EC-Earth performs well and helps making EC-Earth a reliable climate model.

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