2024/09/20: IBM and Nasa Prithvi-WxC Foundation model [link]
2024/08/15: MetMamba, a DLWP model built on a state-of-the-art state-space model, Mamba, offers notable performance gains [link];
2024/07/30: FuXi-S2S published in Nature Communications [link];
2024/06/20: WEATHER-5K: A Large-scale Global Station Weather Dataset Towards Comprehensive Time-series Forecasting Benchmark [link];
2024/05/24: ORCA: A Global Ocean Emulator for Multi-year to Decadal Predictions [link];
2024/05/22: Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling [link];
2024/05/20: Aurora: A Foundation Model of the Atmosphere [link];
2024/05/09: FuXi-ENS: A machine learning model for medium-range ensemble weather forecasting [link];
2024/05/06: CRA5: Extreme Compression of ERA5 for Portable Global Climate and Weather Research via an Efficient Variational Transformer [link];
2024/04/15: ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs [link];
2024/04/12: FuXi-DA: A Generalized Deep Learning Data Assimilation Framework for Assimilating Satellite Observations [link];
2024/03/29: SEEDS: Generative emulation of weather forecast ensembles with diffusion models [link];
2024/03/13: KARINA: An Efficient Deep Learning Model for Global Weather Forecast [link];
2024/02/06: CasCast: Skillful High-resolution Precipitation Nowcasting via Cascaded Modelling [link];
2024/02/04: XiHe, the first data-driven 1/12° resolution global ocean eddy-resolving forecasting model [link];
2024/02/02: ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast [link];
Expand to see more LWMs news
2024/01/28: FengWu-GHR, the first data-driven global weather forecasting model running at the 0.09∘ horizontal resolution [link];
2023/12/27: GenCast, a ML-based generative model for ensemble weather forecasting [link];
2023/12/16: Four-Dimensional Variational (4DVar) assimilation, and develop an AI-based cyclic weather forecasting system, FengWu-4DVar [link];
2023/12/15: FuXi-S2S: An accurate machine learning model for global subseasonal forecasts [link];
2023/12/11: A unified and flexible framework that can equip any type of spatio-temporal models is proposed based on residual diffusion DiffCast [link];
2023/11/13: GCMs are physics-based simulators which combine a numerical solver for large-scale dynamics with tuned representations for small-scale processes such as cloud formation. [link];
NVIDIA Earth2Mip: Earth-2 Model Intercomparison Project (MIP) is a python framework that enables climate researchers and scientists to inter-compare AI models for weather and climate.
AI Models for All: Run AI NWP forecasts hassle-free, serverless in the cloud!
OpenEarthLab: OpenEarthLab, aiming at developing cutting-edge Spatiaotemporal Generation algorithms and promoting the development of Earth Science.