Mechanism learning infers active local evolution rules via prototype-anchored descriptors to achieve more robust forecasting than direct state prediction on benchmarks like Burgers, WeatherBench2, and Lorenz96.
WeatherBench 2: A benchmark for the next generation of data-driven global weather mod- els.arXiv preprint arXiv:2308.15560, 2023
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ESFM is a single open foundation model that unifies heterogeneous Earth data sources and forecasts missing regions while preserving inter-variable physical relationships.
Baguan-solar integrates Baguan weather foundation model forecasts with geostationary satellite data via a decoupled two-stage multimodal framework to deliver kilometer-scale 24-hour solar irradiance predictions, cutting RMSE by 16% versus baselines over East Asia.
HealDA supplies ML-based initial conditions for AI weather models that produce forecasts trailing ERA5-initialized runs by less than one day of effective lead time, with the skill gap arising mainly from initial error size.
citing papers explorer
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Mechanism Learning: Prototype-Anchored Mechanism Inference for Scientific Forecasting
Mechanism learning infers active local evolution rules via prototype-anchored descriptors to achieve more robust forecasting than direct state prediction on benchmarks like Burgers, WeatherBench2, and Lorenz96.
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Earth System Foundation Model (ESFM): A unified framework for heterogeneous data integration and forecasting
ESFM is a single open foundation model that unifies heterogeneous Earth data sources and forecasts missing regions while preserving inter-variable physical relationships.
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Integrating Weather Foundation Model and Satellite to Enable Fine-Grained Solar Irradiance Forecasting
Baguan-solar integrates Baguan weather foundation model forecasts with geostationary satellite data via a decoupled two-stage multimodal framework to deliver kilometer-scale 24-hour solar irradiance predictions, cutting RMSE by 16% versus baselines over East Asia.
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HealDA: Highlighting the importance of initial errors in end-to-end AI weather forecasts
HealDA supplies ML-based initial conditions for AI weather models that produce forecasts trailing ERA5-initialized runs by less than one day of effective lead time, with the skill gap arising mainly from initial error size.