Using Manifold Learning To Understand the Climate System

Prof. Annalisa Bracco

Georgia Institute of Technology

Monday March 27, 2023, 2 PM ET

Abstract:

The threat of global warming and the demand for reliable climate predictions pose a formidable challenge because the climate system is multiscale, high-dimensional and nonlinear. Spatiotemporal recurrences of the system hint to the presence of a low-dimensional manifold containing the high-dimensional climate trajectory that could make the problem more tractable. Here we argue that reproducing the geometrical and topological properties of the low-dimensional attractor should be a key target for models used in climate projections. In doing so, we propose a general data-driven framework to characterize the climate attractor and showcase it in the tropical Pacific Ocean using a reanalysis as observational proxy and two state-of-the-art models. The analysis spans four variables simultaneously over the periods 1979–2019 and 2060–2100. The dynamics is confined on a manifold with dimension lower than the full state space that we characterize through manifold learning algorithms, both linear and nonlinear. The local geometry and local stability of the high-dimensional, multivariable climate attractor are quantified through the local dimension and persistence metrics. Model biases that hamper climate predictability are identified and found to be similar in the two models during the historical period while diverging under the warming scenario considered. The proposed framework provides a comprehensive, physically based, test for assessing climate feedbacks and opens new avenues for improving their model representation.

Biosketch:

Annalisa Bracco is a Professor and Associate Chair for Research in the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology. She obtained her PhD from the University of Genoa in Italy, and worked at the international Center for Theoretical Physics in Trieste and the Woods Hole Oceanographic Institution in Woods Hole, MA before joining the faculty at Georgia Tech.  Dr. Bracco’s research spans a wide range of topics, from geophysical fluid dynamics and physical and biological oceanography to climate change, dynamical systems theory and machine learning.  She is especially interested in carbon-climate, multiscale interactions, and in understanding how climate models may be improved to achieve reliable regional climate projections.

Webinar:

Event site: https://go.umd.edu/bracco

Zoom Webinar: https://go.umd.edu/braccowebinar

Zoom Meeting ID: 961 5444 8928

Zoom password: essic

US Toll: +13017158592
Global call-in numbers: https://umd.zoom.us/u/aMElEpvNu

For IT assistance:
Cazzy Medley: cazzy@umd.edu

Resources:

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Seminar Google calendar: https://go.umd.edu/essicseminarcalendar

Seminar recordings on Youtube: https://www.youtube.com/user/ESSICUMD