← Papers

NeuralGCM

Neural General Circulation Models for Weather and Climate

Paper title Neural General Circulation Models for Weather and Climate

Kochkov et al. (Google Research) · Weather & climate · Public: code, weights

Paper arXiv 2311.07222PDF

A general circulation model in which a differentiable spectral solver computes the large-scale dynamics and neural networks acting on single vertical columns predict the effect of unresolved processes such as clouds, radiation and precipitation. Solver and networks are trained together, end-to-end, on ERA5 trajectories of up to 5 days.

Published
Nature

Share on LinkedIn, X or Bluesky, or or .

Know related work that belongs here?

Something wrong on this page?

More papers

All papers
  1. PhysicsNeMo-Mesh — GPU-Native Meshes and Simulation Cases for Physics AI
  2. Multi-fidelity scaling — Compute-optimal data scaling via multi-fidelity training
  3. CAE-UQ — Predictive Uncertainty for Neural CAE Surrogates