Datasets
This chart shows the spatial variation in the Anomaly Correlation Coefficient (ACC) for the ...
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The reliability diagram shows the reliability of the ECMWF seasonal forecast system (SEAS5) with ...
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This chart shows the Relative Operating Characteristics (ROC) diagram for the three-month ...
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This chart shows the spatial variation in the Relative Operating Characteristics (ROC) skill ...
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The ECMWF seasonal forecasts (SEAS5) are produced every month with a 51-member ensemble at a ...
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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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500-1000 hPa thickness is a measure of the mean temperature of a column of the atmosphere between these pressure levels and can be used to distinguish between warm and cold air masses and...
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Interval/period: Sun, 01/01/1978 - Wed, 10/17/2018
The total ozone estimates are based on solar UV radiation measurements made by ground-based spectrophotometers (Dobson or Brewer type spectrophotometers).
The vertical profiles of ozone concentration are estimated primarily using ozonesonde observations.
Data are available for 159 Dobson stations, 109 Brewer stations and 135 ozonesondes stations.
Interval/period: Tue, 01/01/1924 - Sat, 05/09/2026
(GNSS) radio signals.
The initial data is collected from two in situ ground-based network of GNSS receivers – the International GNSS Service
(IGS) and EUREF Permanent Network (EPN). The IGS collects, archives, and freely distributes GNSS data from a
cooperatively operated global network of more than 500 ground-based GNSS stations since 1994. The EPN is a European
Interval/period: Mon, 01/01/1996 - Sat, 05/09/2026
The first is version 2 of the Integrated Global Radiosounding Archive (IGRA) from 1978 which incorporates global
radiosounding profiles of temperature, humidity and wind from a large number of data sources,
which is 30% larger than the previous version 1. IGRA v2 is the result of quality assurance procedures applied to the
Interval/period: Sun, 01/01/1978 - Sat, 05/09/2026
This diagram gives a measure of the effectiveness of the model in forecasting 500 hPa heights at ...
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The vertically integrated budget diagnostics include the tendencies and lateral fluxes of total energy, water vapour, and latent heat (with the latent heat of vaporization varying with temperature). In addition, the divergences of the lateral fluxes are provided.
Interval/period: Mon, 01/01/1979 - Sat, 05/09/2026
These plots compare recent IFS and experimental AIFS verification scores for 500 hPa ...
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These plots compare recent IFS and experimental AIFS verification scores for 500 hPa ...
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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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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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