Applicants

Professor Dr.-Ing. Tim Ricken
Universität Stuttgart
Institut für Statik und Dynamik der
Luft- und Raumfahrtkonstruktionen (ISD)
Dr. Silke Thoms, Ph.D.
Alfred-Wegener-Institut
Helmholtz-Zentrum für Polar- und Meeresforschung

project description

The seasonal variability of the global sea ice cover is an important component of the global climate. However, the small-scale influence of sea ice is still insufficiently described in global climate models. Therefore, this proposal aims to mathematically describe the key physical (P) and bio-geo-chemical (BGC) processes in sea ice using a high-fidelity two-scale model. The results can then be parameterized and incorporated into global climate models (GCMs), thus improving the predictive power.Ocean warming will significantly change the microstructure of sea ice. Thus, we develop a P-BGC model of an Antarctic sea ice floe to mathematically describe the complex coupled relationships between ice formation, nutrient transport, salinity and brine channel distribution, photosynthesis and carbonate chemistry. We use this model to simulate different scenarios of sea ice formation and its effects on the growth of sea ice algae, which have a significant impact on vertical carbon export (biological carbon pump).Thus, this project contributes significantly to the research topic '3.2.D - Improved understanding of polar processes and mechanisms'. In detail, we address three overarching goals:Step 1: Description of the sea ice structure We use a coupled bi-scale model to describe relevant aspects of freezing and melting in connection with deformation, salinity and brine transport. On the macroscopic level, a continuum mechanical description within the framework of the extended theory of porous media (eTPM) is performed. This allows the description of deformation, transport and reaction processes via a coupled set of partial differential equations (PDE). For the physical phenomenon of phase transformation between water and ice, the phase field model (PF) provides a micro-scale, which also consists of coupled PDEs. This results in a PDE-PDE coupling.Step 2: Coupling with the extended RecoM2 module as micro-scale model This allows the description of the BGC phenomena. The RecoM2 module consists of a system of equations of ordinary differential equations, so that a PDE-ODE coupling to a P-BGC model is performed. Step 3: Evaluation of the model approaches This includes the verification and validation of the combined P-BGC model using literature and experimental data. For the use of the high-resolution two-scale P-BGC model in global climate models the calculation efficiency has to be increased. For this purpose, reduced-order model (ROM) to generate surrogates of the full order model (FOM) are applied, which decrease the model complexity, e.g. by data-driven machine learning (ML) techniques or generalized proper decomposition (GPD).

DFG Programme: Priority Programmes

term since 2021