TRR 181 DFG
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    • Area M Mathematics, New Concepts and Methods
      • M2 Mathematical, Numerical and Datadriven Approaches to Ocean Parameterisations
      • M3 Towards Consistent Subgrid Momentum Closures
      • M5 Reducing Spurious Dissipation and Energetic Inconsistencies in Realistic Ocean Modelling Applications
    • Area T Turbulence and Boundary Layer
      • T2 Ocean Surface Layer Energetics
      • T4 Energy Fluxes at the Air-Sea Interface
      • T5 Gravity Wave Genesis, Break-up and Dissipation
    • Area W Wave Processes
      • W1 Gravity Wave Parameterisation for the Atmosphere
      • W2 Observed and Simulated Internal Tides: Generation, Modification by Eddies, and Contribution to Energy Budget
      • W4 Gravity Wave Parameterisation for the Ocean
      • W5 Internal Wave Energy Dissipation and Wavenumber Spectra: Adaptive Sampling in the Ocean Interior
      • W6 Spectral Energy Fluxes by Wave-Wave Interactions
    • Area L Large-Scale and Balanced Processes
      • L2 Quantifying Dynamical Regimes in the Ocean and the Atmosphere
      • L3 Meso- to Submesoscale Turbulence in the Ocean
      • L4 Multiscale Ocean-Atmosphere Coupling
      • L5 Future Climate Applications of Mixing Parameterisations in Earth-System Models
    • Area S Synthesis with Climate Models
      • S1 Diagnosis and Metrics in Climate Models
      • S2 Improved Parameterisations and Numerics in Climate Models
      • S3 Climate Model Intercomparison
  • Archive
    • Phase 1
      • Area M Mathematics, new concepts and methods
      • Area T Turbulence and boundary layer
      • Area W Wave processes
      • Area L Large-scale and balanced processes
      • Area S Synthesis Climate models as metrics
    • Phase 2
      • Area M Mathematics, New Concepts and Methods
      • Area T Turbulence and Boundary Layer
      • Area W Wave Processes
      • Area L Large-Scale and Balanced Processes
      • Area S Synthesis with Climate Models
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  1. Home
  2. Publications

Publications

Scientific publications are a metric for the success of a project. Our scientists publish in internationally renowned journals and books. Have a look at what has been published so far.

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  • Huang, Y., Fu, Z., & Franzke, C.L.E. (2020). Detecting causality from time series in a machine learning framework. Chaos: An Interdisciplinary Journal of Nonlinear Science 30(6), doi: https://doi.org/10.1063/5.0007670. 

  • Pollmann, F. (2020). Global characterization of the ocean’s internal wave spectrum. J. Phys. Oceanogr. 50(7), doi: https://doi.org/10.1175/JPO-D-19-0185.1.

  • Peng, J.-P., Holtermann, P. & Umlauf, L. (2020). Frontal instability and energy dissipation in a submesoscale upwelling filament. J. Phys. Oceanogr., doi: https://doi.org/10.1175/JPO-D-19-0270.1.

  • Lembo, V., Lucarini, V., & Ragone, F. (2019). Beyond Forcing Scenarios: Predicting Climate Change through Response Operators in a Coupled General Circulation Model. Sci. Rep., doi: 10.1038/S41598-020-65297-2.

  • Kutsenko, A. (2020). An entire function connected with the approximation of the golden ratio. Am. Math. Monthly 127(9), doi: https://doi.org/10.1080/00029890.2020.1801079.

  • de la Vara, A., Cabos, W., Sein, D., Sidorenko, D., Koldunov, N., Koseki, S., Soares, P M. M., & Danilov, S. (2020). On the impact of atmospheric vs oceanic resolutions on the representation of the sea surface temperature in the South Eastern Tropical Atlantic. Clim. Dyn., doi: https://doi.org/10.1007/s00382-020-05256-9.

  • Yousefi, K., Veron, F., & Buckley, M.P. (2020). Momentum flux measurements in the airflow over wind-generated surface waves. J. Fluid Mech. 73, doi: https://doi.org/10.1016/j.euromechflu.2018.04.00.

  • Olbers, D., Jurgenowski, P., & Eden, C. (2020). A wind-driven model of the ocean surface layer with wave radiation physics. Ocean Dynam. 70, doi: https://doi.org/10.1007/s10236-020-01376-2.

  • Akramov, I. & Oliver, M. (2020). On the existence of solutions to a bi-planar Monge–Ampère equation. Acta Math. Sci. 40, 379–388, doi: https://doi.org/10.1007/s10473-020-0206-6.

  • Yang, L., Franzke, C. L., & Fu, Z. (2020). Evaluation of the Ability of Regional Climate Models and a Statistical Model to Represent the Spatial Characteristics of Extreme Precipitation. Int. J. Clim., doi: https://doi.org/10.1002/joc.6602.

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