Climate Emulation

Latest papers

18 papers5 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

Artificial intelligence pathways from weather to climate
Oct 7, 2026Tom Beucler, J. David Neelin, Hui Su +10Climate Emulation Climate Modeling
University of Lausanne, Lausanne, Switzerland. · University of California, Los Angeles, Los Angeles, CA, USA. · Hong Kong University of Science and Technology, Hong Kong SAR, China. +6
EC-EarthFlow: Probabilistic emulation of daily transient global climate model simulations with flow matching
Oct 7, 2026Kirien Whan, Nikolaj T. Mücke, Karin van der WielClimate Emulation Climate Modeling
KNMI, Utrechtseweg 297, De Bilt, 3731GA, The Netherlands · Scientific Computing, Centrum Wiskunde & Informatica, Science Park 123, Amsterdam, 1098XG, The Netherlands · Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, The Netherlands +1
Counterfactual Predictions in Scientific Emulators Without Controlled Experiments
Sep 30, 2026Dingling Yao, Kahaan Gandhi, Valentin Duruisseaux +3Counterfactual Prediction Causal Inference
Institute of Science and Technology Austria · California Institute of Technology · NVIDIA
Learning Hierarchical Causal Representations of the Effects of Forcings on Temperature in Climate Models
Sep 25, 2026Shan Zhao, Ilija Trajkovic, Julia Kaltenborn +4Surrogate Modeling Causal Representation Learning
Technical University of Munich Munich, Germany · Karlsruhe Institute of Technology Karlsruhe, Germany · McGill University & Mila Montreal, Canada +1
HClimRep-Ocean: A Global Ocean Emulator on an Unstructured Mesh
Sep 23, 2026Kacper Nowak, Aleksei Koldunov, Nikolay Koldunov +7Neural Surrogate Modeling Climate Modeling
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany · Forschungszentrum Jülich GmbH, Jülich Supercomputing Center, Jülich, Germany · Karlsruhe Institute of Technology, Karlsruhe, Germany +3
Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulation
Aug 10, 2026Elynn Wu, James P. C. Duncan, Troy Arcomano +11Surrogate Modeling Climate Science
Allen Institute for Artificial Intelligence (Ai2), Seattle, WA, USA · Pacific Northwest National Laboratory, Richland, WA, USA · Los Alamos National Laboratory, Los Alamos, NM, USA +2
Rescene: stable century-long climate emulation from a frozen weather model
Jul 30, 2026Minjong CheonNeural Surrogate Modeling Climate Emulation
Department of Computer Science and Engineering, Sejong University, Seoul, South Korea
Optimal scenario design for climate emulation
Jun 17, 2026Christopher B. Womack, Shahine Bouabid, Andrei Sokolov +4Surrogate Modeling Climate Emulation
Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, United States · Center for Sustainability Science and Strategy, Massachusetts Institute of Technology, Cambridge, MA, United States · Department of Earth, Atmospheric, and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, United States +2
ThousandWorlds: A benchmark for climate emulation of potentially habitable exoplanets
Jun 16, 2026Edward T. Stevenson, Mei Ting Mak, Eric Wolf +4Surrogate Modeling Climate Science
University of Cambridge · University of Oxford · University of Colorado Boulder +3
Regional Climate Model Emulation with Diffusion Approaches: What is the Added Value of Generative Machine Learning?
Jun 12, 2026Mikel N. Legasa, Antoine Doury, Achille Gellens +4Climate Modeling Diffusion Models
Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA/CNRS/UVSQ, Universit´e Paris Saclay, UMR8212, 91191 Gif-sur-Yvette, France · CNRM, Universit´e de Toulouse, M´et´eo-France, CNRS, Toulouse, France · Institut Pierre-Simon Laplace (IPSL), FR636, Paris, France +1
Gaussian Process Latent Factor Regression for Low-Data, High-Dimensional Output Problems
Jun 4, 2026Edward T. Stevenson, Eric T. Wolf, Mei Ting Mak +2Latent Variable Models Climate Emulation
University of Cambridge · University of Colorado Boulder · University of Oxford +1
No Epoch Like the Present: Robust Climate Emulation Requires Out-of-Distribution Generalisation
May 21, 2026Bradley Stanley-Clamp, Anson Lei, Hannah M. Christensen +1Distribution Shift Robustness Climate Science
Applied AI Lab · University of Oxford, UK · Atmospheric, Oceanic and Planetary Physics
Deep Learning Surrogates for Emulating Stochastic Climate Tipping Dynamics
May 20, 2026Adeline Hillier, Jennifer Sleeman, Jay Brett +3Time Series Transformers Multivariate Time Series Forecasting
Johns Hopkins Applied Physics Laboratory Hopkins University · Johns
Towards accurate extreme event likelihoods from diffusion model climate emulators
May 5, 2026Peter Manshausen, Noah Brenowitz, Julius Berner +2Diffusion Model Guidance Climate Science
NVIDIA, Santa Clara, CA, USA
Monthly Diffusion v0.9: A Latent Diffusion Model for the First AI-MIP
Apr 15, 2026Kyle J. C. Hall, Maria J. MolinaClimate Emulation Climate Modeling
Department of Atmospheric & Oceanic Sciences, University of Maryland, College Park, MD 20740
FloeNet: A mass-conserving global sea ice emulator that generalizes across climates
Mar 12, 2026William Gregory, Mitchell Bushuk, James Duncan +8Climate Modeling Climate Emulation
Atmospheric and Oceanic Sciences Program, Princeton University, NJ, USA · Geophysical Fluid Dynamics Laboratory, NOAA, Princeton, NJ, USA · Allen Institute for Artificial Intelligence (Ai2), Seattle, USA +1
Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators
Feb 17, 2026Ankur Mahesh, William D. Collins, Travis A. O'Brien +10Climate Emulation Climate Science
Earth and Planetary Science, University of California, Berkeley, Berkeley, CA, USA. · Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, CA, USA. · Earth and Atmospheric Sciences, Indiana University, Bloomington, IN, USA. +4
ArchesClimate: Probabilistic Decadal Ensemble Generation With Flow Matching
Sep 19, 2025Graham Clyne, Guillaume Couairon, Guillaume Gastineau +2Neural Surrogate Modeling Climate Science
ARCHES, INRIA, Paris, France · UMR LOCEAN, IPSL, Sorbonne Universit´e, IRD, CNRS, MNHN, Paris, France · Department of Computer Science, University of Colorado Boulder, USA

Oct 7, 2026J/K move · Enter open · S save

Artificial intelligence pathways from weather to climate

Tom Beucler, J. David Neelin, Hui Su, Shivanshi Asthana+9

University of Lausanne, Lausanne, Switzerland. · University of California, Los Angeles, Los Angeles, CA, USA. · Hong Kong University of Science and Technology, Hong Kong SAR, China.+6

Climate Emulation Climate Modeling Weather Forecasting

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Deep learning has made rapid advances in weather forecasting: autoregressive models trained on atmospheric reanalyses now rival dynamical models across nowcasting, medium-range, and subseasonal-to-seasonal lead times, producing well-calibrated ensemble forecasts at reduced cost. We review these advances and consider their extension to climate horizons, where the challenge shifts from initial-condition skill to producing reliable statistical responses under altered forcings. AI-powered climate prediction systems must produce credible forced responses to drivers (e.g., greenhouse gases, land-use change) typically outside the observed record. We propose two minimum requirements for AI in climate modeling: (i) external forcing agents must enter explicitly enough to support interventions in which they vary independently; and (ii) robustness must be stress-tested in out-of-distribution regimes, including extremes and counterfactual trajectories. Using leading AI autoregressive emulators and hybrid physics-AI models, we identify development and coupling challenges. Comparing the reported throughput of these models with that of GPU-ported dynamical models highlights how AI can reduce time-to-solution by advancing only the target variables at the required resolution and using longer time steps, rather than integrating a full high-frequency, multivariate state. Diverse AI downscaling strategies can partially substitute for explicit fine-scale resolution, paving the way toward inexpensive local hazard assessment across prediction horizons.