The Atlantic Meridional Overturning Circulation (AMOC) plays a crucial role in shaping the dynamics of the Earth’s climate by distributing heat and nutrients across the Atlantic. It is important to understand the past, present and future changes in the dynamics of the AMOC, either gradual or abrupt, since such changes, and the possibility of its tipping, can have profound climatic and societal impacts. In this regard, big data and AI play an increasingly important role in studying AMOC dynamics based on diverse types of data. These range from geological proxies over contemporary in-situ and remote sensing observations to simulations of state-of-the-art ocean or coupled Earth system models and provide an ever increasing amount of more and more complex data on the AMOC. Advanced numerical methods and AI can help us to uncover critical aspects of the AMOC dynamics by extracting new patterns and highlighting the role of complex physical mechanisms and feedbacks, including early warnings of future regime shifts of the AMOC or some of its subcomponents like the Nordic Seas deep convection or the Northern hemisphere subpolar gyre.
In this session we welcome contributions exploring new ways of using big data and AI to elucidate AMOC dynamics. We aim to cover a broad variety of computational methods, making use of the wealth of AMOC-related observational and/or model data. These can range from statistical methods exploiting big datasets to machine learning and deep learning approaches, including neural-network emulators of the AMOC. The session is open to work on a wide range of timescales, from paleoclimate reconstruction, through current observations to future projections. Contributions may address the analysis of short-term AMOC dynamics, as well as longer-term behaviour, including tipping of the circulation and associated forecast and impact studies.