mlsanityData to 7 Oct 2026

Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data

arXiv 2301.09152 ↗First posted 22 Jan 2023cs.LGcited by 40

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Abstract (arXiv)

To tackle the global climate challenge, it urgently needs to develop a collaborative platform for comprehensive weather forecasting on large-scale meteorological data. Despite urgency, heterogeneous meteorological sensors across countries and regions, inevitably causing multivariate heterogeneity and data exposure, become the main barrier. This paper develops a foundation model across regions capable of understanding complex meteorological data and providing weather forecasting. To relieve the data exposure concern across regions, a novel federated learning approach has been proposed to collaboratively learn a brand-new spatio-temporal Transformer-based foundation model across participants with heterogeneous meteorological data. Moreover, a novel prompt learning mechanism has been adopted to satisfy low-resourced sensors' communication and computational constraints. The effectiveness of the proposed method has been demonstrated on classical weather forecasting tasks using three meteorological datasets with multivariate time series.

Key facts. Cited by 40 papers in the map (data through 7 Oct 2026). Builds on 33 of its 67 references that are in the map. First posted on arXiv 22 Jan 2023.

Builds on

33 of 67 references.

References · 33

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21 more
  1. 2019On the Convergence of FedAvg on Non-IID Datacited by 1,220
  2. 2022FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecastingcited by 1,200
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  4. 2020Adaptive Federated Optimizationcited by 1,036
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  6. 2020A Transformer-based Framework for Multivariate Time Series Representation Learningcited by 449
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  11. 2022PromptFL: Let Federated Participants Cooperatively Learn Prompts Instead of Models -- Federated Learning in Age of Foundation Modelcited by 133
  12. 2021Multi-Center Federated Learning: Clients Clustering for Better Personalizationcited by 112
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  15. 2019Analog forecasting of extreme-causing weather patterns using deep learningcited by 33
  16. 2022On the Convergence of Clustered Federated Learningcited by 31
  17. 2022Personalized Federated Learning With Graphcited by 29
  18. 2023Dual Personalization on Federated Recommendationcited by 19
  19. 2022FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labelscited by 12
  20. 2021Federated Learning for Privacy-Preserving Open Innovation Future on Digital Healthcited by 8
  21. 2020PlumeNet: Large-Scale Air Quality Forecasting Using A Convolutional LSTM Networkcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 8; 2024: 15; 2025: 3; 2026: 14.

40 papers.

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  1. 2024Foundation Models for Time Series Analysis: A Tutorial and Surveycited by 234
  2. 2024Mobile Edge Intelligence for Large Language Models: A Contemporary Surveycited by 125
  3. 2023Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlookcited by 109
  4. 2024Position: What Can Large Language Models Tell Us about Time Series Analysiscited by 47
  5. 2023Foundation Models for Weather and Climate Data Understanding: A Comprehensive Surveycited by 32
  6. 2024Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Modelscited by 23
  7. 2024Federated Large Language Models: Current Progress and Future Directionscited by 22
  8. 2023Federated Prompt Learning for Weather Foundation Models on Devicescited by 17
  9. 2024Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Modelscited by 15
  10. 2024A Survey of Generative Techniques for Spatial-Temporal Data Miningcited by 14
  11. 2024Federated Foundation Models on Heterogeneous Time Seriescited by 13
  12. 2023TempEE: Temporal-Spatial Parallel Transformer for Radar Echo Extrapolation Beyond Auto-Regressioncited by 12
28 more
  1. 2024WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learningcited by 12
  2. 2024Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directionscited by 12
  3. 2025FeDaL: Federated Dataset Learning for General Time Series Foundation Modelscited by 10
  4. 2023ZooPFL: Exploring Black-box Foundation Models for Personalized Federated Learningcited by 9
  5. 2023MASK-CNN-Transformer For Real-Time Multi-Label Weather Recognitioncited by 8
  6. 2024Free Lunch for Federated Remote Sensing Target Fine-Grained Classification: A Parameter-Efficient Frameworkcited by 6
  7. 2024Federated Distillation for Medical Image Classification: Towards Trustworthy Computer-Aided Diagnosiscited by 4
  8. 2026Toward Efficient Membership Inference Attacks against Federated Large Language Models: A Projection Residual Approachcited by 3
  9. 2026Post-Training in Time Series Foundation Models: A Unifying Frameworkcited by 3
  10. 2024HSTFL: A Heterogeneous Federated Learning Framework for Misaligned Spatiotemporal Forecastingcited by 2
  11. 2024Tackling Data Heterogeneity in Federated Time Series Forecastingcited by 2
  12. 2026Bi-level Heterogeneous Learning for Time Series Foundation Models: A Federated Learning Approachcited by 2
  13. 2023Federated Learning on Edge Sensing Devices: A Reviewcited by 1
  14. 2026Reconstructing Training Data from Adapter-based Federated Large Language Modelscited by 1
  15. 2026OmniFM: Toward Modality-Robust and Task-Agnostic Federated Learning for Heterogeneous Medical Imagingcited by 1
  16. 2026Spectral-Aware Text-to-Time Series Generation with Billion-Scale Multimodal Meteorological Datacited by 1
  17. 2026VeinCast: Physics-Guided Dynamic Field Graphs with Graph-Conditioned Fusion for Global Medium-Range Weather Forecastingcited by 1
  18. 2023Take an Irregular Route: Enhance the Decoder of Time-Series Forecasting Transformercited by 0
  19. 2024Less is more: Ensemble Learning for Retinal Disease Recognition Under Limited Resourcescited by 0
  20. 2025A Spatiotemporal Radar-Based Precipitation Model for Water Level Prediction and Flood Forecastingcited by 0
  21. 2025Evaluating Adversarial Attacks on Federated Learning for Temperature Forecastingcited by 0
  22. 2026Optimizing Multi-Agent Weather Captioning via Text Gradient Descent: A Training-Free Approach with Consensus-Aware Gradient Fusioncited by 0
  23. 2026Federated Weather Modeling on Sensor Datacited by 0
  24. 2026Earth Science Foundation Models: From Perception to Reasoning and Discoverycited by 0
  25. 2026FM2: Unified Federated Foundation Models for Heterogeneous Multimodal Medical Imagingcited by 0
  26. 2026Lethe: How Hard Is It to Forget? A Benchmark for Federated Unlearning in Medical Imagingcited by 0
  27. 2026F2STNet: Fair and Federated Spectral-Temporal Modeling for Graph Forecastingcited by 0
  28. 2026Copy What Is Seen, Generate What Is Not: Training-Free Anomaly-Aware Video Restorationcited by 0