Distinguished Seminar in Computational Science and Engineering
October 12, 2023, 12 PM
A New Generation of Global Climate Models Augmented by AI
Laure Zanna
Professor of Mathematics & Atmosphere/Ocean Science
New York University
Abstract:
Climate simulations have long been invaluable in understanding and predicting global and regional climate change. Their fidelity has been limited by computing capabilities leading to inaccurate parametrizations of key unresolved processes such as convection, cloud, or mixing, and, consequently, to biases in large-scale phenomena such as temperature, rainfall, and sea level. These unresolved processes have posed a significant hurdle in enhancing climate simulations and their predictions.
A promising paradigm shift is now underway, fueled by the explosion of climate data and the formidable potential of machine learning (ML) algorithms to parametrize subgrid processes in climate models. Here, we will present a suite of global simulations in which machine-learning parameterizations replace, or augment, ad-hoc representations of ocean and sea-ice subgrid processes. The simulations are performed with the NOAA-Geophysical Fluid Dynamics Laboratory’s MOM6-based global climate models OM4 and CM4. We will discuss how the data-driven parameterizations of ocean mixing and sea-ice affect large-scale biases and variability of relevant climate fields, and associated mechanisms. This new generation of data-informed simulations has the potential to provide more reliable climate projections at global and local scales. This is collaborative work as part of M2LInES:https://m2lines.github.io/
Bio:
Laure Zanna is a Professor in Mathematics & Atmosphere/Ocean Science at the Courant Institute, New York University. Prior to NYU, she was a faculty member at the University of Oxford until 2019, and obtained her PhD in 2009 in Climate Dynamics from Harvard University. Her research focuses on the role of the ocean in climate, in particular ocean heat uptake, sea level rise, turbulence, climate modeling, and uncertainty quantification. She is the lead principal investigator and scientific director of M²LInES – an international collaboration to improve climate models with scientific machine learning support by Schmidt Futures and the Geoscience Director of the NSF Science and Technology Center LEAP. She received the 2020 Nicholas P. Fofonoff Award from the American Meteorological Society “For exceptional creativity in the development and application of new concepts in ocean and climate dynamics”.
A New Generation of Global Climate Models Augmented by AI
Laure Zanna
Professor of Mathematics & Atmosphere/Ocean Science
New York University
10/12/23