Climate Physics: Insights from Theory, Models, and AI
FOCUS · MAR-C52 · ID: 3998176
Presentations
-
Machine Learning for Climate Modeling
ORAL · Invited
–
Publication: Dagon, K., B.M. Sanderson, R.A. Fisher, D.M. Lawrence (2020), A machine learning approach to emulation and biophysical parameter estimation with the Community Land Model, version 5, Advances in Statistical Climatology, Meteorology and Oceanography, 6, 223-244, https://doi.org/10.5194/ascmo-6-223-2020.
Dagon, K., J. Truesdale, J.C. Biard, K.E. Kunkel, G.A. Meehl, and M.J. Molina (2022), Machine learning-based detection of weather fronts and associated extreme precipitation in historical and future climates, Journal of Geophysical Research: Atmospheres, 127, e2022JD037038, https://doi.org/10.1029/2022JD037038.
Kennedy, D., K. Dagon, D.M. Lawrence, R.A. Fisher, B.M. Sanderson, N. Collier, et al. (2025), One-at-a-time parameter perturbation ensemble of the Community Land Model, version 5.1, Journal of Advances in Modeling Earth Systems, 17, e2024MS004715, https://doi.org/10.1029/2024MS004715.Presenters
-
Katie Dagon
- NSF National Center for Atmospheric Research
Authors
-
Katie Dagon
- NSF National Center for Atmospheric Research
-
-
Teaching AI weather models to forecast gray swan extreme events
ORAL
–
Presenters
-
Pedram Hassanzadeh
- University of Chicago
Authors
-
Pedram Hassanzadeh
- University of Chicago
-
Amaury Lancelin
- ENS
-
Alex Wikner
- UChicago
-
Dorian S Abbot
- UChicago
-
Jonathan Weare
- Courant Institute of Mathematical Sciences
-
Freddy Bouchet
- CNRS
-
Willow Stenglein
- UT Austin
-
Y. Qiang Sun
- UChicago
-
Laurent Dubus
- RTE
-
-
Physical Climate Storylining in the Introductory Undergraduate Classroom: a transdisciplinary approach
ORAL
–
Publication: Planned paper after study is complete at the end of 2025
Presenters
-
Vandana Singh
- Framingham State University
Authors
-
Vandana Singh
- Framingham State University
-
-
Using Surface Temperature Data to Teach Data Time Series Analysis
ORAL
–
Presenters
-
Joseph J Trout
- Stockton University
Authors
-
Joseph J Trout
- Stockton University
-
Maxim J Wunder
- Stockton University
-
Gabriel Tagiaroli
- Stockton University
-
Olivia Williams
- Stockton University
-
-
Nonlinear mechanism of climatic variability
ORAL
–
Presenters
-
Perrin Wesley Davidson
- Massachusetts Institute of Technology
Authors
-
Perrin Wesley Davidson
- Massachusetts Institute of Technology
-
Daniel Harris Rothman
- Massachusetts Institute of Technology
-
-
A Simple Model to Understand and Assess the Increase in the Earth's Energy Imbalance
ORAL
–
Publication: The abstract reports on work extending
C. Taylor, "Separating Greenhouse-Gas Driven Forcing from Natural Fluctuations in the Time Series for Global Mean Temperatures", submitted to PRL, manuscript LD19563, revised version currently under review.
A new paper detailing the work reported on in the submitted abstract is currently in preparation.Presenters
-
Cyrus Cooper Taylor
- Case Western Reserve University
Authors
-
Cyrus Cooper Taylor
- Case Western Reserve University
-
-
Examining Earth's Fast Radiative Feedbacks Using Machine-Learning-Based Emulators of the Climate System
ORAL
–
Publication: A. Mahesh, W. D. Collins, B. Bonev, N. Brenowitz, Y. Cohen, J. Elms, P. Harrington,
K. Kashinath, T. Kurth, J. North, T. O'Brien, M. Pritchard, D. Pruitt, M. Risser, S. Sub-
ramanian, and J. Willard. Huge ensembles—Part 1: Design of ensemble weather forecasts
using spherical Fourier neural operators. Geoscientific Model Development, 18(17):5575–
5603, 2025, doi:10.5194/gmd-18-5575-2025.
A. Mahesh, W. D. Collins, B. Bonev, N. Brenowitz, Y. Cohen, P. Harrington, K. Kashinath,
T. Kurth, J. North, T. A. O'Brien, M. Pritchard, D. Pruitt, M. Risser, S. Subramanian, and
J. Willard. Huge ensembles—Part 2: Properties of a huge ensemble of hindcasts generated
with spherical Fourier neural operators. Geoscientific Model Development, 18(17):5605–
5633, 2025, doi:10.5194/gmd-18-5605-2025.
Bonev, B., T. Kurth, A. Mahesh, M. Bisson, J. Kossaifi, K. Kashinath, A. Anandkumar, W.D. Collins, M. Pritchard, and A. Keller, 2025: FourCastNet 3: A principled approach to probabilistic machine-learning weather forecast at scale. Submitted to arXiv.org,
doi:10.48550/arXiv.2507.12144.Presenters
-
William D Collins
- University of California, Berkeley and Lawrence Berkeley National Laboratory
Authors
-
William D Collins
- University of California, Berkeley and Lawrence Berkeley National Laboratory
-
Ankur Mahesh
- University of California, Berkeley and Lawrence Berkeley National Laboratory
-
Travis A O'Brien
- Earth and Atmospheric Sciences, Indiana University
-
Paul Goddard
- Earth and Atmospheric Sciences, Indiana University
-
Sinclair Zebaze
- Earth and Atmospheric Sciences, Indiana University
-
Shashank Subramanian
- NERSC, Lawrence Berkeley National Laboratory
-
James P Duncan
- Allen Institute for Artificial Intelligence (Ai2)
-
Oliver Watt-Meyer
- Allen Institute for Artificial Intelligence (Ai2)
-
Boris Bonev
- NVIDIA
-
Thorsten Kurth
- NVIDIA
-
Karthik Kashinath
- NVIDIA
-
Michael S Pritchard
- NVIDIA Research & University of California, Irvine
-
-
Abstract Withdrawn
ORAL · Withdrawn
–
-
Heterogeneity of the Attractor of the Lorenz '96 Model: Lyapunov Analysis, Unstable Periodic Orbits, and Shadowing Properties
ORAL
–
Publication: C. C. Maiocchi, V. Lucarini, A. Gritsun. Y. Sato, Heterogeneity of the attractor of the Lorenz '96 model: Lyapunov analysis, unstable periodic orbits, and shadowing properties, Physica D 457, 133970 (2024) https://doi.org/10.1016/j.physd.2023.133970
Presenters
-
Valerio Lucarini
- University of Leicester
Authors
-
Valerio Lucarini
- University of Leicester
-
Yuzuru Sato
- Hokkaido University
-
Chiara C Maiocchi
- London Business School
-
Andrey Gritsun
- Marchuk Institute of Numerical Mathematics - Russian Academy of Sciences
-