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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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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This dataset provides daily mid-morning measurements for Lake Surface Water Temperature (LSWT) derived from satellite observations. LSWT, together with five other variables (lake ice cover and thickness, water leaving reflectance, water level and extent) is recognised as the Essential Climate Variable (ECV) "Lakes" by the Global Climate Observing System (GCOS). LSWT is a key parameter in determining lake ecological conditions as it influences physical, chemical and biological processes.

calendar_today Interval/period: Thu, 06/01/1995 - Sat, 05/09/2026

This dataset provides lake water levels for 311 selected lakes on four continents derived from satellite radar altimetry.

calendar_today Interval/period: Wed, 01/01/1992 - 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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Mean wave period is the spectrally averaged period of the waves. Wave periods are shown in seconds using colour shading – click on the middle icon to the bottom right for the scale...

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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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The Essential Climate Variables for assessment of climate variability from 1979 to present dataset contains a selection of climatologies, monthly anomalies and monthly mean fields of Essential Climate Variables (ECVs) suitable for monitoring and assessment of climate variability and change. Selection criteria are based on accuracy and temporal consistency on monthly to decadal time scales.

calendar_today Interval/period: Mon, 01/01/1979 - Wed, 04/01/2026

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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