{"total":218,"rows":[{"id":"2312.15796","title":"GenCast: Diffusion-based ensemble forecasting for medium-range weather","created":"2023-12-25","cited_by_count":177,"area":null},{"id":"2312.03876","title":"Scaling transformer neural networks for skillful and reliable medium-range weather forecasting","created":"2023-12-06","cited_by_count":110,"area":null},{"id":"2411.11268","title":"ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses","created":"2024-11-18","cited_by_count":54,"area":null},{"id":"2502.00338","title":"OneForecast: A Universal Framework for Global and Regional Weather Forecasting","created":"2025-02-01","cited_by_count":34,"area":null},{"id":"2409.13598","title":"Prithvi WxC: Foundation Model for Weather and Climate","created":"2024-09-20","cited_by_count":31,"area":null},{"id":"2402.00059","title":"FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting","created":"2024-01-28","cited_by_count":30,"area":null},{"id":"2405.16297","title":"LUCIE: A Lightweight Uncoupled ClImate Emulator with long-term stability and physical consistency for O(1000)-member ensembles","created":"2024-05-25","cited_by_count":30,"area":null},{"id":"2406.04759","title":"Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks","created":"2024-06-07","cited_by_count":30,"area":null},{"id":"2410.05431","title":"Continuous Ensemble Weather Forecasting with Diffusion models","created":"2024-10-07","cited_by_count":30,"area":null},{"id":"2406.16947","title":"Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales","created":"2024-06-19","cited_by_count":27,"area":null},{"id":"2410.14932","title":"Can AI weather models predict out-of-distribution gray swan tropical cyclones?","created":"2024-10-19","cited_by_count":26,"area":null},{"id":"2404.17752","title":"Generative Diffusion-based Downscaling for Climate","created":"2024-04-27","cited_by_count":25,"area":null},{"id":"2503.13502","title":"Foundation Models for Spatio-Temporal Data Science: A Tutorial and Survey","created":"2025-03-12","cited_by_count":24,"area":null},{"id":"2312.12462","title":"Towards an end-to-end artificial intelligence driven global weather forecasting system","created":"2023-12-18","cited_by_count":21,"area":null},{"id":"2406.14798","title":"Probabilistic Emulation of a Global Climate Model with Spherical DYffusion","created":"2024-06-21","cited_by_count":21,"area":null},{"id":"2408.05472","title":"FuXi Weather: A data-to-forecast machine learning system for global weather","created":"2024-08-10","cited_by_count":21,"area":null},{"id":"2501.06907","title":"Deep Learning and Foundation Models for Weather Prediction: A Survey","created":"2025-01-12","cited_by_count":16,"area":null},{"id":"2601.18111","title":"Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting","created":"2026-01-26","cited_by_count":15,"area":null},{"id":"2404.17652","title":"Validating Deep Learning Weather Forecast Models on Recent High-Impact Extreme Events","created":"2024-04-26","cited_by_count":14,"area":null},{"id":"2405.15412","title":"Data-driven Global Ocean Modeling for Seasonal to Decadal Prediction","created":"2024-05-24","cited_by_count":14,"area":null},{"id":"2508.15724","title":"Numerical models outperform AI weather forecasts of record-breaking extremes","created":"2025-08-21","cited_by_count":14,"area":null},{"id":"2505.13755","title":"Panda: A pretrained forecast model for chaotic dynamics","created":"2025-05-19","cited_by_count":13,"area":null},{"id":"2512.24440","title":"Towards mechanistic understanding in a data-driven weather model: internal activations reveal interpretable physical features","created":"2025-12-30","cited_by_count":12,"area":null},{"id":"2604.09041","title":"U-Cast: A Surprisingly Simple and Efficient Frontier Probabilistic AI Weather Forecaster","created":"2026-04-10","cited_by_count":12,"area":null},{"id":"2409.18529","title":"Robustness of AI-based weather forecasts in a changing climate","created":"2024-09-27","cited_by_count":11,"area":null},{"id":"2502.07532","title":"Diffusion-LAM: Probabilistic Limited Area Weather Forecasting with Diffusion","created":"2025-02-11","cited_by_count":11,"area":null},{"id":"2506.04528","title":"Hierarchical Implicit Neural Emulators","created":"2025-06-05","cited_by_count":10,"area":null},{"id":"2509.26258","title":"EnScale: Temporally-consistent multivariate generative downscaling via proper scoring rules","created":"2025-09-30","cited_by_count":10,"area":null},{"id":"2405.02154","title":"Neural Context Flows for Meta-Learning of Dynamical Systems","created":"2024-05-03","cited_by_count":9,"area":null},{"id":"2410.12938","title":"Local Off-Grid Weather Forecasting with Multi-Modal Earth Observation Data","created":"2024-10-16","cited_by_count":9,"area":null},{"id":"2411.16098","title":"Global spatio-temporal downscaling of ERA5 precipitation through generative AI","created":"2024-11-22","cited_by_count":9,"area":null},{"id":"2506.07003","title":"End-to-End Probabilistic Framework for Learning with Hard Constraints","created":"2025-06-08","cited_by_count":9,"area":null},{"id":"2511.23043","title":"High-Resolution Probabilistic Data-Driven Weather Modeling with a Stretched-Grid","created":"2025-11-28","cited_by_count":9,"area":null},{"id":"2411.10191","title":"FengWu-W2S: A deep learning model for seamless weather-to-subseasonal forecast of global atmosphere","created":"2024-11-15","cited_by_count":8,"area":null},{"id":"2502.04406","title":"Calibrated Physics-Informed Uncertainty Quantification","created":"2025-02-06","cited_by_count":8,"area":null},{"id":"2503.03038","title":"Generative assimilation and prediction for weather and climate","created":"2025-03-04","cited_by_count":8,"area":null},{"id":"2505.16620","title":"CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models","created":"2025-05-22","cited_by_count":8,"area":null},{"id":"2412.18097","title":"LangYa: Revolutionizing Cross-Spatiotemporal Ocean Forecasting","created":"2024-12-24","cited_by_count":7,"area":null},{"id":"2505.18671","title":"Self-Supervised Evolution Operator Learning for High-Dimensional Dynamical Systems","created":"2025-05-24","cited_by_count":7,"area":null},{"id":"2506.12045","title":"From Proxies to Fields: Spatiotemporal Reconstruction of Global Radiation from Sparse Sensor Sequences","created":"2025-05-24","cited_by_count":7,"area":null},{"id":"2410.06560","title":"Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting","created":"2024-10-09","cited_by_count":6,"area":null},{"id":"2502.13185","title":"CondensNet: Enabling stable long-term climate simulations via hybrid deep learning models with adaptive physical constraints","created":"2025-02-18","cited_by_count":6,"area":null},{"id":"2506.05513","title":"Geometric and Physical Constraints Synergistically Enhance Neural PDE Surrogates","created":"2025-06-05","cited_by_count":6,"area":null},{"id":"2506.10868","title":"A multi-scale loss formulation for learning a probabilistic model with proper score optimisation","created":"2025-06-12","cited_by_count":6,"area":null},{"id":"2506.22552","title":"Probing forced responses and causality in data-driven climate emulators: conceptual limitations and the role of reduced-order models","created":"2025-06-27","cited_by_count":6,"area":null},{"id":"2507.03578","title":"SciVid: Cross-Domain Evaluation of Video Models in Scientific Applications","created":"2025-07-04","cited_by_count":6,"area":null},{"id":"2510.23111","title":"Neural Emulator Superiority: When Machine Learning for PDEs Surpasses its Training Data","created":"2025-10-27","cited_by_count":6,"area":null},{"id":"2409.18885","title":"HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting","created":"2024-09-27","cited_by_count":5,"area":null},{"id":"2410.00812","title":"Generative causal testing to bridge data-driven models and scientific theories in language neuroscience","created":"2024-10-01","cited_by_count":5,"area":null},{"id":"2410.23667","title":"Projected Neural Differential Equations for Learning Constrained Dynamics","created":"2024-10-31","cited_by_count":5,"area":null},{"id":"2411.15101","title":"What You See is Not What You Get: Neural Partial Differential Equations and The Illusion of Learning","created":"2024-11-22","cited_by_count":5,"area":null},{"id":"2505.17720","title":"PEAR: Equal Area Weather Forecasting on the Sphere","created":"2025-05-23","cited_by_count":5,"area":null},{"id":"2509.17601","title":"FastNet: Improving the physical consistency of machine-learning weather prediction models through loss function design","created":"2025-09-22","cited_by_count":5,"area":null},{"id":"2604.16429","title":"(Sparse) Attention to the Details: Preserving Spectral Fidelity in ML-based Weather Forecasting Models","created":"2026-04-06","cited_by_count":5,"area":null},{"id":"2606.10642","title":"PhysMetrics.Weather: An Evaluation Framework for Physical Consistency in ML Weather Models","created":"2026-06-09","cited_by_count":5,"area":null},{"id":"2311.10665","title":"Online Calibration of Deep Learning Sub-Models for Hybrid Numerical Modeling Systems","created":"2023-11-17","cited_by_count":4,"area":null},{"id":"2311.18348","title":"Reconstructing Historical Climate Fields With Deep Learning","created":"2023-11-30","cited_by_count":4,"area":null},{"id":"2407.05232","title":"PAPM: A Physics-aware Proxy Model for Process Systems","created":"2024-07-07","cited_by_count":4,"area":null},{"id":"2412.00486","title":"Automatic Differentiation-based Full Waveform Inversion with Flexible Workflows","created":"2024-11-30","cited_by_count":4,"area":null},{"id":"2501.00738","title":"Learning Physically Interpretable Atmospheric Models from Data with WSINDy","created":"2025-01-01","cited_by_count":4,"area":null},{"id":"2509.00010","title":"CERA: A Framework for Improved Generalization of Machine Learning Models to Changed Climates","created":"2025-08-15","cited_by_count":4,"area":null},{"id":"2509.01879","title":"MAUSAM: An Observations-focused assessment of Global AI Weather Prediction Models During the South Asian Monsoon","created":"2025-09-02","cited_by_count":4,"area":null},{"id":"2510.13050","title":"An Operational Deep Learning System for Satellite-Based High-Resolution Global Nowcasting","created":"2025-10-15","cited_by_count":4,"area":null},{"id":"2601.21151","title":"Learning to Advect: A Neural Semi-Lagrangian Architecture for Weather Forecasting","created":"2026-01-29","cited_by_count":4,"area":null},{"id":"2602.05287","title":"Position: Universal Time Series Foundation Models Rest on a Category Error","created":"2026-02-05","cited_by_count":4,"area":null},{"id":"2603.12449","title":"FloeNet: A mass-conserving global sea ice emulator that generalizes across climates","created":"2026-03-12","cited_by_count":4,"area":null},{"id":"2605.30184","title":"Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts","created":"2026-05-28","cited_by_count":4,"area":null},{"id":"2406.15076","title":"Neural Incremental Data Assimilation","created":"2024-06-21","cited_by_count":3,"area":null},{"id":"2411.14677","title":"Exploring the Use of Machine Learning Weather Models in Data Assimilation","created":"2024-11-22","cited_by_count":3,"area":null},{"id":"2502.19611","title":"PRDP: Progressively Refined Differentiable Physics","created":"2025-02-26","cited_by_count":3,"area":null},{"id":"2503.03142","title":"A Survey of Foundation Models for Environmental Science","created":"2025-03-05","cited_by_count":3,"area":null},{"id":"2504.09940","title":"TianQuan-S2S: A Subseasonal-to-Seasonal Global Weather Model via Incorporate Climatology State","created":"2025-04-14","cited_by_count":3,"area":null},{"id":"2505.14555","title":"Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting","created":"2025-05-20","cited_by_count":3,"area":null},{"id":"2506.03744","title":"Probabilistic measures afford fair comparisons of AIWP and NWP model output","created":"2025-06-04","cited_by_count":3,"area":null},{"id":"2506.10660","title":"Constructing Extreme Heatwave Storylines with Differentiable Climate Models","created":"2025-06-12","cited_by_count":3,"area":null},{"id":"2507.03176","title":"Deep Learning Atmospheric Models Reliably Simulate Out-of-Sample Land Heat and Cold Wave Frequencies","created":"2025-07-03","cited_by_count":3,"area":null},{"id":"2509.02061","title":"LUCIE-3D: A three-dimensional climate emulator for forced responses","created":"2025-09-02","cited_by_count":3,"area":null},{"id":"2510.27066","title":"AI-boosted rare event sampling to characterize extreme weather","created":"2025-10-31","cited_by_count":3,"area":null},{"id":"2512.18815","title":"Controllable Probabilistic Forecasting with Stochastic Decomposition Layers","created":"2025-12-21","cited_by_count":3,"area":null},{"id":"2602.03767","title":"Decision-oriented benchmarking to transform AI weather forecast access: Application to the Indian monsoon","created":"2026-02-03","cited_by_count":3,"area":null},{"id":"2602.03924","title":"WIND: Weather Inverse Diffusion for Zero-Shot Atmospheric Modeling","created":"2026-02-03","cited_by_count":3,"area":null},{"id":"2605.06916","title":"Tyche: One Step Flow for Efficient Probabilistic Weather Forecasting","created":"2026-05-07","cited_by_count":3,"area":null},{"id":"2605.08856","title":"Controlling Transient Amplification Improves Long-horizon Rollouts","created":"2026-05-09","cited_by_count":3,"area":null},{"id":"2605.14546","title":"Discovering Physical Directions in Weight Space: Composing Neural PDE Experts","created":"2026-05-14","cited_by_count":3,"area":null},{"id":"2501.03840","title":"Machine learning applications in archaeological practices: a review","created":"2025-01-07","cited_by_count":2,"area":null},{"id":"2504.00307","title":"Generating realistic global precipitation fields from modelled atmospheric circulation","created":"2025-04-01","cited_by_count":2,"area":null},{"id":"2504.14422","title":"Optimal Lattice Boltzmann Closures through Multi-Agent Reinforcement Learning","created":"2025-04-19","cited_by_count":2,"area":null},{"id":"2505.24429","title":"Deep Learning Weather Models for Subregional Ocean Forecasting: A Case Study on the Canary Current Upwelling System","created":"2025-05-30","cited_by_count":2,"area":null},{"id":"2506.16281","title":"Artificial Intelligence for Atmospheric Sciences: A Research Roadmap","created":"2025-06-19","cited_by_count":2,"area":null},{"id":"2509.09052","title":"MoWE : A Mixture of Weather Experts","created":"2025-09-10","cited_by_count":2,"area":null},{"id":"2509.14563","title":"Learning to Retrieve for Environmental Knowledge Discovery: An Augmentation-Adaptive Self-Supervised Learning Framework","created":"2025-09-18","cited_by_count":2,"area":null},{"id":"2509.14775","title":"FlowCast-ODE: Continuous Hourly Weather Forecasting with Dynamic Flow Matching and ODE Solver","created":"2025-09-18","cited_by_count":2,"area":null},{"id":"2510.00282","title":"Electron neural closure for turbulent magnetosheath simulations: energy channels","created":"2025-09-30","cited_by_count":2,"area":null},{"id":"2510.19110","title":"Signature Kernel Scoring Rule: A Spatio-Temporal Diagnostic for Probabilistic Weather Forecasting","created":"2025-10-21","cited_by_count":2,"area":null},{"id":"2511.17427","title":"Towards fully differentiable neural ocean model with Veros","created":"2025-11-21","cited_by_count":2,"area":null},{"id":"2602.01736","title":"Position: The Inevitable End of One-Architecture-Fits-All-Domains in Time Series Forecasting","created":"2026-02-02","cited_by_count":2,"area":null},{"id":"2602.15004","title":"PDE foundation models are skillful AI weather emulators for the Martian atmosphere","created":"2026-02-16","cited_by_count":2,"area":null},{"id":"2602.16090","title":"Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators","created":"2026-02-17","cited_by_count":2,"area":null},{"id":"2603.07893","title":"Designing probabilistic AI monsoon forecasts to inform agricultural decision-making","created":"2026-03-09","cited_by_count":2,"area":null},{"id":"2605.08935","title":"PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting","created":"2026-05-09","cited_by_count":2,"area":null}],"next_cursor":"100"}