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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The 850 hPa level is usually just above the boundary layer and at this level the day-night variation in temperature is generally negligible...
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This chart shows 7-day mean anomalies of 500hPa geopotential height from the ECMWF Sub-seasonal ...
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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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Various thermall comfort parameters showing thermal comfort
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This chart shows 7-day mean anomalies of temperature at 10hPa from the ECMWF Sub-seasonal range ...
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The ECMWF seasonal forecasts (SEAS5) are produced every month with a 51-member ensemble at ...
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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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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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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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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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Cloud base height is derived by upwardly searching the structure of the model atmosphere to find the altitude where the cloud fraction becomes >1% and...
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Divergence of horizontal air flow or winds is a measure of the spreading out of air at a particular point. Divergence is +ve where air spreads out; –ve where air converges...
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The 850 hPa level is usually just above the boundary layer and at this level the day-night variation in temperature is generally negligible...
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