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Search: WFRF:(Schmith Torben)

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1.
  • Döscher, Ralf, et al. (author)
  • The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6
  • 2022
  • In: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 15:7, s. 2973-3020
  • Journal article (peer-reviewed)abstract
    • The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond.
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2.
  • Sterl, Andreas, et al. (author)
  • A look at the ocean in the EC-Earth climate model
  • 2012
  • In: Climate Dynamics. - : Springer Science and Business Media LLC. - 0930-7575 .- 1432-0894. ; 39:11, s. 2631-2657
  • Journal article (peer-reviewed)abstract
    • 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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3.
  • Schmith, Torben, et al. (author)
  • Limited predictability of extreme decadal changes in the Arctic Ocean freshwater content
  • 2018
  • In: Climate Dynamics. - : Springer Science and Business Media LLC. - 0930-7575 .- 1432-0894. ; 51:9-10, s. 3927-3942
  • Journal article (peer-reviewed)abstract
    • Predictability of extreme changes in the Arctic Ocean freshwater content and the associated release into the subpolar North Atlantic up to one decade ahead is investigated using a CMIP5-type global climate model. The perfect-model setup consists of a 500 year control run, from which selected 10 year long segments are predicted by initialized, perturbed ensemble predictions. Initial conditions for these are selected from the control run to represent large positive or negative decadal changes in the total freshwater content in the Arctic Ocean. Two different classes of ensemble predictions are performed, one initialized with the ‘observed’ ocean globally, and one initialized with the model climatology in the Arctic Ocean and with the observed ocean elsewhere. Analysis reveals that the former yields superior predictions 1 year ahead as regards both liquid freshwater content and sea ice volume in the Arctic Ocean. For prediction years two and above there is no overall gain in predictability from knowing the initial state in the Arctic Ocean and damped persistence predictions perform just as well as the ensemble predictions. Areas can be identified, mainly in the proper Canadian and Eurasian basins, where knowledge of the initial conditions gives a gain in predictability of liquid freshwater content beyond year two. Total freshwater export events from the Arctic Ocean into the subpolar North Atlantic have no predictability even 1 year ahead. This is a result of the sea ice component not being predictable and LFW being on the edge of being predictable for prediction time 1 year.
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