Energy does not vanish
The energy of a closed system is steady. It is not lost but rather converted into other forms, such as when kinetic energy is transferred into thermal energy or vice versa heat results in a force.
However, this fundamental principle of natural science is often still a problem for climate research. For example, in case of the calculation of ocean currents, where small-scale vortices as well as mixing processes they induce need to be considered, without fully understanding where the energy for their creation originates from. This is similar in the atmosphere, the only difference being that air is moving instead of water. Again, local turbulences can drive larger movements or vice versa waves on a larger scale can disintegrate into small structures.
All these processes are important for the Earth’s climate and determine how temperatures will rise in the future.
Being Part of the Team: What TRR 181 PhDs say
Existing climate models show energetic and mathematical inconsistencies which may lead to fundamental errors in climate forecasts. Now is the right time to combine recent efforts in Meteorology, Oceanography and applied Mathematics and to go new ways.
In August 2022, Janina Tenhaus did a research stay at the Alfred C. Glassell, Jr. SUSTAIN Laboratory in Miami, USA.
Our newsletter comes out every three months and includes information about the work done in our project and more.
The Young Researchers Meeting (YRM) and the annual M-Day took place in Hamburg on Dec 8 and 9, 2022.
Brecht, R. & Bihlo, A. (2023). Computing the Ensemble Spread From Deterministic Weather Predictions Using Conditional Generative Adversarial Networks. Geophysical Research Letters 50(2), e2022GL101452, doi: https://doi.org/10.1029/2022GL101452.
Juricke, S., Bellinghausen, K., Danilov, S., Kutsenko, A., & Oliver, M. (2023). Scale analysis on unstructured grids: Kinetic energy and dissipation power spectra on triangular meshes. Journal of Advances in Modeling Earth Systems 15, e2022MS003280, doi: https://doi.org/10.1029/2022MS003280.
Pohlmann, H., Brune, S., Fröhlich, K., Jungclaus, J.H., Sgoff, C. & Baehr, J. (2022). Impact of ocean data assimilation on climate predictions with ICON-ESM. Clim Dyn, doi: https://doi.org/10.1007/s00382-022-06558-w.