SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators
Not on the map. Why?
Abstract (arXiv)
Traditional numerical global climate models simulate the full Earth system by exchanging boundary conditions between separate simulators of the atmosphere, ocean, sea ice, land surface, and other geophysical processes. This paradigm allows for distributed development of individual components within a common framework, unified by a coupler that handles translation between realms via spatial or temporal alignment and flux exchange. Following a similar approach adapted for machine learning-based emulators, we present SamudrACE: a coupled global climate model emulator which produces centuries-long simulations at 1-degree horizontal, 6-hourly atmospheric, and 5-daily oceanic resolution, with 145 2D fields spanning 8 atmospheric and 19 oceanic vertical levels, plus sea ice, surface, and top-of-atmosphere variables. SamudrACE is highly stable and has low climate biases comparable to those of its components with prescribed boundary forcing, with realistic variability in coupled climate phenomena such as ENSO that is not possible to simulate in uncoupled mode.
Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 9 of its 40 references that are in the map. First posted on arXiv 15 Sep 2025.
Builds on
9 of 40 references.
References · 9
- 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
- 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 4,993
- 2022FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operatorscited by 748
- 2023FuXi: A cascade machine learning forecasting system for 15-day global weather forecastcited by 237
- 2023ACE: A fast, skillful learned global atmospheric model for climate predictioncited by 53
- 2024ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responsescited by 53
- 2023AI-GOMS: Large AI-Driven Global Ocean Modeling Systemcited by 26
- 2024Samudra: An AI Global Ocean Emulator for Climatecited by 26
- 2024Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Modelcited by 20
Built on by
Citing papers per year: 2025: 4; 2026: 11.
15 papers.
Sort:
By area:
- 2026FloeNet: A mass-conserving global sea ice emulator that generalizes across climatescited by 4
- 2025ArchesClimate: Probabilistic Decadal Ensemble Generation With Flow Matchingcited by 3
- 2025Long-Range Distillation: Distilling 10,000 Years of Simulated Climate into Long Timestep AI Weather Modelscited by 2
- 2025Genomic Next-Token Predictors are In-Context Learnerscited by 1
- 2025Crowdsourcing the Frontier: Advancing Hybrid Physics-ML Climate Simulation via a 50,000 Kaggle Competitioncited by 1
- 2026Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulatorscited by 1
- 2026Samudra 2: Scaling Ocean Emulators across Resolutionscited by 1
- 2026How Can Machine Learning Emulators Best Support Climate Science?cited by 0
- 2026Toward Artificial Intelligence Enabled Earth System Couplingcited by 0
- 2026Assessing Emulator Design and Training for Modal Aerosol Microphysics Parameterizations in E3SMv2cited by 0
- 2026OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecastingcited by 0
- 2026Emulating the Forced Response of Climate Models with Generative Machine Learningcited by 0
3 more
- 2026Recursive Flow Matchingcited by 0
- 2026Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulationcited by 0
- 2026Artificial intelligence pathways from weather to climatecited by 0
- 2026Artificial intelligence pathways from weather to climate7 Oct 2026
- 2026Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulation10 Aug 2026
- 2026Recursive Flow Matching26 May 2026
- 2026Samudra 2: Scaling Ocean Emulators across Resolutions24 May 2026
- 2026Emulating the Forced Response of Climate Models with Generative Machine Learning16 May 2026
- 2026OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecasting12 May 2026
- 2026Assessing Emulator Design and Training for Modal Aerosol Microphysics Parameterizations in E3SMv223 Apr 2026
- 2026Toward Artificial Intelligence Enabled Earth System Coupling26 Mar 2026
- 2026How Can Machine Learning Emulators Best Support Climate Science?20 Mar 2026
- 2026FloeNet: A mass-conserving global sea ice emulator that generalizes across climates12 Mar 2026
- 2026Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators17 Feb 2026
- 2025Long-Range Distillation: Distilling 10,000 Years of Simulated Climate into Long Timestep AI Weather Models28 Dec 2025
- 2025ArchesClimate: Probabilistic Decadal Ensemble Generation With Flow Matchingcited by 3
- 2026Recursive Flow Matchingcited by 0
- 2026Recursive Flow Matching26 May 2026
- 2025ArchesClimate: Probabilistic Decadal Ensemble Generation With Flow Matching19 Sep 2025
- 2026FloeNet: A mass-conserving global sea ice emulator that generalizes across climatescited by 4
- 2025Long-Range Distillation: Distilling 10,000 Years of Simulated Climate into Long Timestep AI Weather Modelscited by 2
- 2025Genomic Next-Token Predictors are In-Context Learnerscited by 1
- 2025Crowdsourcing the Frontier: Advancing Hybrid Physics-ML Climate Simulation via a 50,000 Kaggle Competitioncited by 1
- 2026Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulatorscited by 1
- 2026Samudra 2: Scaling Ocean Emulators across Resolutionscited by 1
- 2026How Can Machine Learning Emulators Best Support Climate Science?cited by 0
- 2026Toward Artificial Intelligence Enabled Earth System Couplingcited by 0
- 2026Assessing Emulator Design and Training for Modal Aerosol Microphysics Parameterizations in E3SMv2cited by 0
- 2026OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecastingcited by 0
- 2026Emulating the Forced Response of Climate Models with Generative Machine Learningcited by 0
- 2026Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulationcited by 0
12 most cited of 13 All 13 (JSON)
- 2026Artificial intelligence pathways from weather to climate7 Oct 2026
- 2026Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulation10 Aug 2026
- 2026Samudra 2: Scaling Ocean Emulators across Resolutions24 May 2026
- 2026Emulating the Forced Response of Climate Models with Generative Machine Learning16 May 2026
- 2026OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecasting12 May 2026
- 2026Assessing Emulator Design and Training for Modal Aerosol Microphysics Parameterizations in E3SMv223 Apr 2026
- 2026Toward Artificial Intelligence Enabled Earth System Coupling26 Mar 2026
- 2026How Can Machine Learning Emulators Best Support Climate Science?20 Mar 2026
- 2026FloeNet: A mass-conserving global sea ice emulator that generalizes across climates12 Mar 2026
- 2026Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators17 Feb 2026
- 2025Long-Range Distillation: Distilling 10,000 Years of Simulated Climate into Long Timestep AI Weather Models28 Dec 2025
- 2025Crowdsourcing the Frontier: Advancing Hybrid Physics-ML Climate Simulation via a 50,000 Kaggle Competition26 Nov 2025
12 newest of 13 All 13 (JSON)