Datasets
ECMWF is now running version 2 of its Artificial Intelligence Forecasting System (AIFS). The AIFS consists of a deterministic model, AIFS Single, and an ensemble model, AIFS ENS.
The deterministic model has been running operationally since 25 February 2025 and was upgraded from AIFS Single v1.1 to AIFS Single v2 on 12 May 2026. Further details can be found on the dedicated Implementation of AIFS Single v1 page.
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This chart provides information on the verification of forecasts of Accumulated Cyclone Energy ...
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The ECMWF seasonal forecasts (SEAS5) are produced every month with a 51-member ensemble at a ...
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These charts show surface pressure patterns. Areas of high pressure (anticyclones) are usually associated with settled weather...
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Various thermall comfort parameters showing thermal comfort
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Bulk Wind Shearcharts show the vector value (in wind arrow form) of the shear between the low level, near surface level (10 m) and a mid-tropospheric level (about 6 km)...
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The surface wind is influenced by the roughness of the earth's surface and is likely to be less strong, and a little backed (in the northern hemisphere) or veered (in the southern hemisphere)...
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This chart shows the anomaly in the wind speed at 10 m above the earth's surface (in m/s) ...
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These charts show surface pressure patterns. Areas of high pressure (anticyclones) are usually associated with settled weather...
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Air temperatures at 2 m above the earth's surface approximate most closely to the conditions a person would most likely experience...
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Aurora: a deep learning-based system developed by Microsoft. It is initialised with ECMWF analysis. Aurora operates at 0.1° resolution.
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Aurora: a deep learning-based system developed by Microsoft. It is initialised with ECMWF analysis. Aurora operates at 0.1° resolution.
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Aurora: a deep learning-based system developed by Microsoft. It is initialised with ECMWF analysis. Aurora operates at 0.1° resolution.
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FourCastNet v2-small:a deep learning-based system developed by NVIDIA in collaboration with researchers at several US universities.It is initialised with ECMWF analysis. FourCastNet operates at 0.25° resolution.
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FourCastNet v2-small:a deep learning-based system developed by NVIDIA in collaboration with researchers at several US universities.It is initialised with ECMWF analysis. FourCastNet operates at 0.25° resolution.
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FourCastNet v2-small:a deep learning-based system developed by NVIDIA in collaboration with researchers at several US universities.It is initialised with ECMWF analysis. FourCastNet operates at 0.25° resolution.
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FourCastNet v2-small:a deep learning-based system developed by NVIDIA in collaboration with researchers at several US universities.It is initialised with ECMWF analysis. FourCastNet operates at 0.25° resolution.
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GraphCast (Google DeepMind): a deep learning-based system developed by Google DeepMind.It is initialised with ECMWF analysis. GraphCast operates at 0.25° resolution.
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GraphCast (Google DeepMind): a deep learning-based system developed by Google DeepMind.It is initialised with ECMWF analysis. GraphCast operates at 0.25° resolution.
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The CAT (Clear Air Turbulence) parameter is given in units of the turbulent Eddy Dissipation Rate (EDR), product shows EDR values on selected flight levels overlayed with wind speeds.
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This chart shows the probability that both the wind at 10 m above the earth's surface is ...
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This chart shows the probability that both the wind at 10 m above the earth's surface is ...
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This chart shows the probability that both the wind at 10 m above the earth's surface is ...
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These diagrams compare Continuous Ranked Probability Skill Scores (CRPSS) of ECMWF with ...
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Bulk Wind Shear charts show the scalar value of the shear between the winds at the two pressure levels selected. Shear can be useful in assessing the strength of a front or...
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