AWI-CM3 to AWI-ESM3: Expanding Degrees of Freedom in Kilometer-Scale Climate Modeling

Earth system modeling is vital for understanding the Earth's complex processes and predicting climate change impacts. These models require high degrees of freedom to accurately represent interactions and feedbacks among the atmosphere, oceans, and biosphere. This complexity is essential for generating reliable climate projections, informing policy, and developing adaptation strategies.
In this context, the recent development of the AWI-CM3, a coupled atmosphere-ocean general circulation model (AOGCM), marks a significant advancement in climate modeling, addressing the need for improved accuracy and resolution. The AWI-CM3 outperforms CMIP6 standards at low resolution (~100 km) and demonstrates impressive capabilities for high-resolution simulations, with global coupled models evaluated at resolutions of 31 km and 9 km, and a 4.5 km resolution model currently running. 
Our ongoing efforts further reflect this commitment to complexity and precision. Here, we present results from the recent upgrade to OpenIFS 48r1, integrating cutting-edge features from NWP/ECMWF to improve core atmospheric processes. This upgrade strengthens the model’s capacity to simulate weather extremes, atmospheric dynamics, and precipitation patterns with greater fidelity. Additionally, we evaluate the first major step in the evolution from AWI-CM3 to AWI-ESM3: enhancing the model through dynamic vegetation coupling with LPJ-Guess 4.1.2. This integration allows for more realistic simulations of vegetation feedbacks, and land-atmosphere interactions, which are essential for accurately capturing long-term climate trends and ecosystem changes.
Looking ahead, the incorporation of ice sheet dynamics using the Parallel Ice Sheet Model (PISM) will extend the capabilities of our Earth System Model, AWI-ESM3, enabling more comprehensive climate projections. Parallel work is ongoing to couple the ocean biogeochemistry model FESOM2/RECOM with the atmospheric carbon cycle, providing a more holistic representation of the carbon-climate feedbacks. Additionally, integrating CMIP7 forcing datasets will further align the model with the latest climate modeling standards, reinforcing its role in advancing both regional and global climate assessments.