Synthesis Area S: Climate models as metrics

Our scientists in Area S will implement new parameterisations and numerics into two national leading coupled climate models and test their performance. Therefore, they provide a metric for the success of the whole project.

Synthesis of all areas

During the course of the project, Area S will use the results (e.g. new parameterizations or refined model set ups) of the other areas in the projects to further enhance and improve climate models.

  • Li, X., Lorenz M., Klingbeil, K., Chrysagi, E., Gräwe, U., Wu, J. Burchard, H. (2022). Salinity Mixing and Diahaline Exchange Flow in A Large Multi-outlet Estuary with Islands. J. Phys. Oceanogr.doi: https://doi.org/10.1175/JPO-D-21-0292.1.

  • Gutjahr, O., Jungclaus, J. H., Brüggemann, N., Haak, H. & Marotzke, J. (2022). Air-Sea Interactions and Water Mass Transformation During a Katabatic Storm in the Irminger Sea.  J. Geophys. Res.- Oceans 127, e2021JC018075, doi: https://doi.org/10.1029/2021JC018075.

  • Nagavciuc, V., Scholz, P. & Ionita, M. (2022). Hotspots for warm and dry summers in Romania. Nat. Hazards Earth Syst. Sci. 22(4), 1347–1369, doi: https://doi.org/10.5194/nhess-22-1347-2022.

  • Hutter, N., Bouchat, A., Koldunov, N., Losch, M. et al. (2022). Sea Ice Rheology Experiment (SIREx): 2. Evaluating linear kinematic features in high-resolution sea ice simulations. J. Geophys. Res.- Oceans 127, e2021JC017666, doi: https://doi.org/10.1029/2021JC017666

  • Jungclaus, J. H., Brüggemann, N., Gutjahr, O., von Storch, J.S., Korn, P. et al. (2022). The ICON Earth System Model Version 1.0. J. Adv. Model Earth Sy. 14, e2021MS002813, doi: https://doi.org/10.1029/2021MS002813.

  • Khosravi, N., Wang, Q., Koldunov, N., Danilov, S., Jung, T. et al. (2022). The Arctic Ocean in CMIP6 models: Biases and projected changes in temperature and salinity. Earth's Future 10(2), e2021EF002282, doi: https://doi.org/10.1029/2021EF002282

  • Danilov, S., Mehlmann, C. & Fofonova, V. (2022). On discretizing sea-ice dynamics on triangular meshes using vertex, cell or edge velocities. Ocean Modelling 170, 101937, doi: https://doi.org/10.1016/j.ocemod.2021.101937.

  • Dima, M., Lohmann, G., Scholz, P. et al. (2022). AMOC modes linked with distinct North Atlantic deep water formation sites. Clim. Dyn. 59, 837–849, doi: https://doi.org/10.1007/s00382-022-06156-w.

  • Scholz, P., Sidorenko, D., Danilov, S., Wang, Q., Koldunov, N., Sein, D., & Jung, T. (2022). Assessment of the Finite-VolumE Sea ice–Ocean Model (FESOM2.0) – Part 2: Partial bottom cells, embedded sea ice and vertical mixing library CVMix. Geosci. Model Dev. 15(2), 335–363, doi: https://doi.org/10.5194/gmd-15-335-2022.

  • Schmid, F., Gagarina, E., Klein, R. & Achatz, U. (2021). Toward a Numerical Laboratory for Investigations of Gravity Wave–Mean Flow Interactions in the Atmosphere. Mon. Wea. Rev. 149, 4005–4026, doi: https://doi.org/10.1175/MWR-D-21-0126.1.