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The Earth system model CLIMBER-X v1.0-Part 1: climate model description and validation

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2022-07-28
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Copernicus Gesellschaft MBH
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The newly developed fast Earth system model CLIMBER-X is presented. The climate component of CLIMBER-X consists of a 2.5-D semi-empirical statistical– dynamical atmosphere model, a 3-D frictional–geostrophic ocean model, a dynamic–thermodynamic sea ice model and a land surface model. All the model components are discretized on a regular lat–long grid with a horizontal resolution of 5^(◦) × 5^(◦) . The model has a throughput of ∼ 10 000 simulation years per day on a single node with 16 CPUs on a high-performance computer and is designed to simulate the evolution of the Earth system on temporal scales ranging from decades to > 100 000 years. A comprehensive evaluation of the model performance for the present day and the historical period shows that CLIMBER-X is capable of realistically reproducing many observed climate characteristics, with results that generally lie within the range of state-of-theart general circulation models. The analysis of model performance is complemented by a thorough assessment of climate feedbacks and model sensitivities to changes in external forcings and boundary conditions. Limitations and applicability of the model are critically discussed. CLIMBER-X also includes a detailed representation of the global carbon cycle and is coupled to an ice sheet model, which will be described in separate papers. CLIMBER-X is available as open-source code and is expected to be a useful tool for studying past climate changes and for the investigation of the long-term future evolution of the climate.
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© Author(s) 2022. Matteo Willeit was supported by the German Science Foundation (DFG) grant GA 1202/2-1 and by the BMBF-funded project PalMod. Alexander Robinson was funded by the Ramón y Cajal Programme of the Spanish Ministry for Science, Innovation and Universities (grant no. RYC-2016-20587). We thank the World Climate Research Programme, which, through its Working Group on Coupled Modelling, coordinated and promoted CMIP5 and CMIP6. We thank the climate modelling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP5, CMIP6 and ESGF. Xavier Fettweiss is thanked for providing the grain size data from simulations of the regional climate model MAR. Data from the RAPID AMOC monitoring project are funded by the Natural Environment Research Council and are freely available from http://www.rapid.ac.uk/rapidmoc (last access: 15 January 2022). This research has been supported by the Bundesministerium für Bildung und Forschung (grant no. PalMod), the Deutsche Forschungsgemeinschaft (grant no. GA 1202/2-1), and the Ministerio de Ciencia e Innovación (grant no. RYC-2016- 20587). The publication of this article was funded by the Open Access Fund of the Leibniz Association.
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