mlsanityData to 7 Oct 2026

SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators

arXiv 2509.12490 ↗First posted 15 Sep 2025physics.ao-ph cs.LGcited by 15

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

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  2. 2016SGDR: Stochastic Gradient Descent with Warm Restartscited by 4,993
  3. 2022FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operatorscited by 748
  4. 2023FuXi: A cascade machine learning forecasting system for 15-day global weather forecastcited by 237
  5. 2023ACE: A fast, skillful learned global atmospheric model for climate predictioncited by 53
  6. 2024ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responsescited by 53
  7. 2023AI-GOMS: Large AI-Driven Global Ocean Modeling Systemcited by 26
  8. 2024Samudra: An AI Global Ocean Emulator for Climatecited by 26
  9. 2024Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Modelcited by 20

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 11.

15 papers.

Sort:

By area: