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Building understanding from the ground up: hierarchical modelling of the climate system

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If you have a question about this talk, please contact Aleksandr Sahakyan.

Earth’s climate system is fantastically complex, involving numerous coupled physical, chemical, and biological systems that can interact across a wide range of spatial and temporal scales. Climate modellers attempt to get a handle on this knotty structure by constructing mathematical representations of the climate system, which are often realised on high-performance computing setups. Such sophisticated numerical representations are crucially important for making accurate and precise predictions about the future state of Earth’s climate, but there is an inherent danger in increasing the level of complexity in any model. It is unfortunately easy to create a climate model that is nearly as inscrutable as the climate system itself. If we want to fully understand the dynamics of the climate system, a different approach is required.

As a complement to assembling collections of intricate, realistic models, we can consider model hierarchies in which models of increasing complexity are compared with one another. For the sake of clarity and simplicity, the models at the base of the hierarchy should only capture the essential dynamics of the system or process in question while avoiding too many refinements. Models further up the hierarchy include additional sources of complexity and aim to be more realistic. Isaac Held and others have explored the idea of “hierarchical modelling” in depth. In this talk, we examine a few model hierarchies from oceanography and climate science, including a model of how the global ocean adjusts to changes in wind stress at the surface and a basic model of climate sensitivity.

This talk is part of the Darwin College Sciences Group series.

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