Weather Forecasting
5개 벤치마크 · 논문 579편 · 이 태스크의 논문 보기 →
Benchmarks
Most implemented
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
GraphCast: Learning skillful medium-range global weather forecasting
Chickenpox Cases in Hungary: a Benchmark Dataset for Spatiotemporal Signal Processing with Graph Neural Networks
WeatherBench: A benchmark dataset for data-driven weather forecasting
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
Probabilistic Weather Forecasting with Hierarchical Graph Neural Networks
Papers
Varda-single-1.0: deterministic data-driven weather forecasting at 1 km resolution over Switzerland's complex topography
We present Varda-single-1.0, a medium-range data-driven weather prediction system built for the Alpine domain. It provides hourly deterministic regional forecasts on a mesh of 1 km resolution and global forecasts on a 31…
Weather ForecastingRecursive self-improvement of AI research agents
AI agents are beginning to automate research and development across the AI stack, from improving training efficiency to optimizing inference. A natural next step is to improve the research efficiency of the agents themse…
Weather ForecastingAsyncCouple-Flow: Asynchronous Cross-Modal Coupling and Flow Matching for Spatio-Temporal Forecasting
Multi-modal spatio-temporal forecasting (MM-STF) supports weather nowcasting, traffic prediction, and earth-system modeling by combining heterogeneous sources such as physical fields, satellite imagery, and in-situ senso…
Semantic SimilarityWeather ForecastingTraffic PredictionUncertainty-Aware End-to-End AI Weather Forecasting: Disentangling Observation and Model Contributions
End-to-end weather forecasting systems produce skillful global gridded and station forecasts directly from raw Earth observations, replacing the numerical weather prediction pipeline, including data assimilation, at a fr…
Weather ForecastingBridging short- and medium-range weather forecasting with machine learning
The National Oceanic and Atmospheric Administration (NOAA) employs independent prediction systems for distinct forecast products. While some separation is practical, we argue that combining short- and medium-range weathe…
Weather ForecastingTimestep-Conditioned Transformers for Global Weather Forecasting
Existing machine-learning weather forecasting models rely on predetermined and fixed autoregressive timesteps. The choice of model timestep involves a fundamental trade-off: shorter timesteps (e.g. 1 to 6 hours) finely r…
Weather Forecasting