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High-Latitude Application and Testing of Earth System Models (HiLAT-RASM)

Funding Program Area(s)
Project Type
Laboratory Science Focus Area (SFA)
Project Term
to
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Visualization of ocean, sea ice, and atmosphere interactions in the Barents Sea, as simulated by E3SM-Arctic, the Arctic-focused configuration of E3SM developed by the HiLAT-RASM team. The figure shows ocean temperature (colors), sea ice concentration (gray shading), and atmospheric circulation (green ‘streamlets’). Courtesy of Francesca Samsel and Greg Abram (TACC).
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Schematic representation of the HiLAT-RASM Phase III research plan. The three Science Areas are interconnected by the unifying framework that consists of the three Capability Areas together to understand and quantify complex feedbacks on Arctic Amplification.

The High-Latitude Application and Testing of Earth System Models (HiLAT) Science Focus Area (SFA) is teaming up again with the Regional Arctic System Model (RASM) project to study feedbacks that contribute to Arctic Amplification. This accelerated warming of the Arctic is having major and unprecedented impacts on every aspect of the Arctic Earth system. Our ability to anticipate these changes is hampered by incomplete knowledge of the complex Earth system feedbacks that modulate Arctic warming and by the challenges of translating this knowledge into model fidelity. 

The HiLAT-RASM Phase III aims to improve our ability to project future Arctic changes by developing a unifying framework to understand, quantify, and compare complex Earth system feedbacks that modulate Arctic warming, and to improve the model representation of such feedbacks. The unifying framework is designed to examine feedbacks across two dimensions. We will investigate feedbacks from a wide range of processes represented by three Science Areas, namely meridional exchanges of heat and moisture between high and low latitudes; complex regional feedbacks between the ocean, sea ice, and atmosphere; and complex feedbacks between the terrestrial, aquatic, and biogeochemical domains. In addition, we will study individual feedbacks across models with a range of complexities represented by three Capability Areas, namely from broad-ranging multi-model examination in the CMIP6 ensemble; through detailed investigation in our higher-resolution models E3SM-Arctic (DOE E3SM model with refined meshes in the Arctic) and RASM; to intuitive and efficient Machine Learning-assisted Energy Balance Models.

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