Symmetric Composition of Anisotropic Operators for Global Subseasonal-to-Seasonal Climate Forecasting

arXiv:2602.15040 · physics.ao-ph, cs.LG · Submitted 2026-02-04 · Read on arXiv

physics.ao-ph, cs.LG

Submitted: 2026-02-04

Updated: 2026-09-27

Code: https://github.com/ecmwf-lab/aimodels

Terminology

• Transformer — 20× in this paper · explained in 2 episodes
• Accuracy — 12× in this paper · explained in 1 episode
• Benchmark — 6× in this paper · explained in 2 episodes
• Foundation Model — 6× in this paper · explained in 3 episodes
• Latent Representation — 6× in this paper · explained in 2 episodes
• Decoupling — 5× in this paper · explained in 2 episodes
• Fidelity — 5× in this paper · explained in 2 episodes
• Fourier Neural Operator — 5× in this paper
• Aggregation — 4× in this paper · explained in 1 episode
• Robustness — 4× in this paper · explained in 5 episodes
• Symmetric Orthogonal Operator Network — 4× in this paper
• Ablation — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Foundation Models — 3× in this paper · explained in 7 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• AdamW Optimizer — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Benchmarking — 2× in this paper · explained in 3 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Discrete Fourier Transform — 2× in this paper
• Embeddings — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Numerical Weather Prediction — 2× in this paper
• Tokenization — 2× in this paper · explained in 2 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Anomaly Correlation Coefficient — 1× in this paper
• Attention Mechanism — 1× in this paper · explained in 2 episodes
• Chaotic Dynamics — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Integrated Forecasting System — 1× in this paper
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Latitude-weighted Root Mean Square Error — 1× in this paper
• Ordinary Differential Equations (ODEs) — 1× in this paper · explained in 2 episodes
• Probabilistic Forecasting — 1× in this paper · explained in 3 episodes
• Systematic Bias — 1× in this paper · explained in 3 episodes
• Time Series Forecasting — 1× in this paper · explained in 3 episodes

Sources

• Layer Normalization
• FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead
• Language Modeling with Gated Convolutional Networks
• An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
• AIFS -- ECMWF's data-driven forecasting system
• TianQuan-S2S: A Subseasonal-to-Seasonal Global Weather Model via Incorporate Climatology State
• Fourier Neural Operator for Parametric Partial Differential Equations
• ClimaX: A foundation model for weather and climate
• FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
• Root Mean Square Layer Normalization
• Mesh Interpolation Graph Network for Dynamic and Spatially Irregular Global Weather Forecasting

Related papers

• NORi: An ML-Augmented Ocean Boundary Layer Parameterization
• A Checklist to assess the energy and carbon impacts of ML/AI applications in Earth System Modeling
• On the Predictive Skill of Artificial Intelligence-based Weather Models for Extreme Events using Uncertainty Quantification
• A Mechanism-Coupled Split Window Network for Medium- to High-Resolution Land Surface Temperature Retrieval
• Composable multi-satellite precipitation estimation for evolving observing systems
• Improving global precipitation forecasts with an AI weather model trained on satellite observations