mlsanityData to 7 Oct 2026

Forecasting Global Weather with Graph Neural Networks

arXiv 2202.07575 ↗First posted 15 Feb 2022physics.ao-ph cs.LGcited by 165

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Abstract (arXiv)

We present a data-driven approach for forecasting global weather using graph neural networks. The system learns to step forward the current 3D atmospheric state by six hours, and multiple steps are chained together to produce skillful forecasts going out several days into the future. The underlying model is trained on reanalysis data from ERA5 or forecast data from GFS. Test performance on metrics such as Z500 (geopotential height) and T850 (temperature) improves upon previous data-driven approaches and is comparable to operational, full-resolution, physical models from GFS and ECMWF, at least when evaluated on 1-degree scales and when using reanalysis initial conditions. We also show results from connecting this data-driven model to live, operational forecasts from GFS.

Key facts. Cited by 165 papers in the map (data through 7 Oct 2026). Builds on 19 of its 34 references that are in the map. First posted on arXiv 15 Feb 2022.

Builds on

19 of 34 references.

References · 19

  1. 2020Fourier Neural Operator for Parametric Partial Differential Equationscited by 2,806
  2. 2018Relational inductive biases, deep learning, and graph networkscited by 1,341
  3. 2020Learning Mesh-Based Simulation with Graph Networkscited by 840
  4. 2021Machine learning accelerated computational fluid dynamicscited by 461
  5. 2022Message Passing Neural PDE Solverscited by 368
  6. 2020Discovering Symbolic Models from Deep Learning with Inductive Biasescited by 335
  7. 2021Skillful Precipitation Nowcasting using Deep Generative Models of Radarcited by 308
  8. 2020WeatherBench: A benchmark dataset for data-driven weather forecastingcited by 272
  9. 2020Solver-in-the-Loop: Learning from Differentiable Physics to Interact with Iterative PDE-Solverscited by 201
  10. 2020MetNet: A Neural Weather Model for Precipitation Forecastingcited by 128
  11. 2020Improving data-driven global weather prediction using deep convolutional neural networks on a cubed spherecited by 95
  12. 2021Gradients are Not All You Needcited by 82
7 more
  1. 2021Sub-seasonal forecasting with a large ensemble of deep-learning weather prediction modelscited by 76
  2. 2019Machine Learning for Precipitation Nowcasting from Radar Imagescited by 56
  3. 2021Variational Data Assimilation with a Learned Inverse Observation Operatorcited by 28
  4. 2021Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networkscited by 20
  5. 2021Combining distribution-based neural networks to predict weather forecast probabilitiescited by 18
  6. 2021MS-nowcasting: Operational Precipitation Nowcasting with Convolutional LSTMs at Microsoft Weathercited by 12
  7. 2021Machine Learning Emulation of 3D Cloud Radiative Effectscited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 13; 2023: 38; 2024: 50; 2025: 38; 2026: 26.

165 papers.

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  1. 2023ClimaX: A foundation model for weather and climatecited by 325
  2. 2022GraphCast: Learning skillful medium-range global weather forecastingcited by 261
  3. 2023Neural General Circulation Models for Weather and Climatecited by 232
  4. 2023WeatherBench 2: A benchmark for the next generation of data-driven global weather modelscited by 227
  5. 2023PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solverscited by 205
  6. 2022Towards Multi-spatiotemporal-scale Generalized PDE Modelingcited by 190
  7. 2022FourCastNet: Accelerating Global High-Resolution Weather Forecasting using Adaptive Fourier Neural Operatorscited by 188
  8. 2023FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Leadcited by 170
  9. 2023GenCast: Diffusion-based ensemble forecasting for medium-range weathercited by 169
  10. 2022Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecastcited by 164
  11. 2023A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detectioncited by 145
  12. 2023Scaling transformer neural networks for skillful and reliable medium-range weather forecastingcited by 106
38 more
  1. 2023DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecastingcited by 105
  2. 2022MultiScale MeshGraphNetscited by 94
  3. 2022Clifford Neural Layers for PDE Modelingcited by 91
  4. 2024ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEscited by 78
  5. 2023Deep Learning for Day Forecasts from Sparse Observationscited by 70
  6. 2023Graph Neural Networks for temporal graphs: State of the art, open challenges, and opportunitiescited by 60
  7. 2023ACE: A fast, skillful learned global atmospheric model for climate predictioncited by 53
  8. 2023ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modelingcited by 46
  9. 2023SwinRDM: Integrate SwinRNN with Diffusion Model towards High-Resolution and High-Quality Weather Forecastingcited by 32
  10. 2023Foundation Models for Weather and Climate Data Understanding: A Comprehensive Surveycited by 32
  11. 2022SwinVRNN: A Data-Driven Ensemble Forecasting Model via Learned Distribution Perturbationcited by 31
  12. 2024On the Foundations of Earth and Climate Foundation Modelscited by 31
  13. 2024FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecastingcited by 30
  14. 2024LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability and physical consistency for O(1000)-member ensemblescited by 30
  15. 2024DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systemscited by 29
  16. 2024Probabilistic Weather Forecasting with Hierarchical Graph Neural Networkscited by 29
  17. 2023W-MAE: Pre-trained weather model with masked autoencoder for multi-variable weather forecastingcited by 28
  18. 2023Advancing Parsimonious Deep Learning Weather Prediction using the HEALPix Meshcited by 27
  19. 2024Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scalescited by 27
  20. 2024Foundation Models for the Electric Power Gridcited by 27
  21. 2025Fixing the Double Penalty in Data-Driven Weather Forecasting Through a Modified Spherical Harmonic Loss Functioncited by 27
  22. 2024A Practical Probabilistic Benchmark for AI Weather Modelscited by 25
  23. 2023Provably Powerful Graph Neural Networks for Directed Multigraphscited by 24
  24. 2024Uncertainty quantification for data-driven weather modelscited by 24
  25. 2024Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modelingcited by 23
  26. 2023Graph-based Neural Weather Prediction for Limited Area Modelingcited by 22
  27. 2023Scaling Spherical CNNscited by 21
  28. 2024Probabilistic Emulation of a Global Climate Model with Spherical DYffusioncited by 21
  29. 2025Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaoscited by 21
  30. 2024Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Modelcited by 20
  31. 2024Regional data-driven weather modeling with a global stretched-gridcited by 20
  32. 2024Huge Ensembles Part I: Design of Ensemble Weather Forecasts using Spherical Fourier Neural Operatorscited by 17
  33. 2022WeatherBench Probability: A benchmark dataset for probabilistic medium-range weather forecasting along with deep learning baseline modelscited by 16
  34. 2024Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Modelscited by 15
  35. 2025Deep Learning and Foundation Models for Weather Prediction: A Surveycited by 15
  36. 2022Spatial Mixture-of-Expertscited by 14
  37. 2023Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systemscited by 14
  38. 2025CirT: Global Subseasonal-to-Seasonal Forecasting with Geometry-inspired Transformercited by 13

50 most cited of 165 All 165 (JSON)