the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Variability and extremes: statistical validation of the Alfred Wegener Institute Earth System Model (AWI-ESM)
Thorsten Dickhaus
Gerrit Lohmann
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For 1 century, the hemispheric summer insolation is proposed as a key pacemaker of astronomical climate change. However, an increasing number of geologic records reveal that the low-latitude hydrological cycle shows asynchronous precessional evolutions that are very often out of phase with the summer insolation. Here, we propose that the astronomically driven low-latitude hydrological cycle is not paced by summer insolation but by shifting perihelion.
Our study examines the Atlantic Meridional Overturning Circulation (AMOC) during the Last Glacial Maximum (LGM), a period with higher tidal dissipation. Despite increased tidal mixing, our model simulations show that the AMOC remained relatively shallow, consistent with paleoproxy data and resolving previous inconsistencies between proxy data and model simulations. This research highlights the importance of strong ocean stratification during the LGM and its interaction with tidal mixing.
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Inaccuracies in air–sea heat fluxes severely degrade the accuracy of ocean numerical simulations. Here, we use artificial neural networks to correct air–sea heat fluxes as a function of oceanic and atmospheric state predictors. The correction successfully improves surface and subsurface ocean temperatures beyond the training period and in prediction experiments.
FINAM is not a model), a new coupling framework written in Python to dynamically connect independently developed models. Python, as the ultimate glue language, enables the use of codes from nearly any programming language like Fortran, C++, Rust, and others. FINAM is designed to simplify the integration of various models with minimal effort, as demonstrated through various examples ranging from simple to complex systems.
This study introduces a new 3D lake–ice–atmosphere coupled model that significantly improves winter climate simulations for the Great Lakes compared to traditional 1D lake model coupling. The key contribution is the identification of critical hydrodynamic processes – ice transport, heat advection, and shear-driven turbulence production – that influence lake thermal structure and ice cover and explain the superior performance of 3D lake models to their 1D counterparts.