AI summaryExamines connections between weather forecasting and climate modelling, including unresolved issues in physical consistency, generalisation, transparency and computational cost.
Weather and climateCross-scale modellingPhysical consistency
AI summaryPretrains on diverse geophysical data and adapts to forecasting weather, ocean waves, air quality and tropical cyclone tracks, exploring a foundation model for multiple Earth-system tasks.
AI summaryTakes observations directly as input and produces global gridded and local station forecasts, connecting several stages of weather prediction in a trainable system.
AI summaryCombines a differentiable dynamical core with neural-network parameterisations to study weather forecasting and climate simulation, including physical consistency over long integrations.
AI summaryIntroduces a three-dimensional architecture for Earth data and hierarchical temporal aggregation, improving medium-range forecasts under the study’s reanalysis-based evaluation and reducing iterative errors.