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At any location over the oceans, there is a spectrum of waves which describes how much wave energy is present for given wave frequencies and direction of propagation...

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Significant wave height can be shown to correspond to the average wave height of the top one-third highest waves. The wave period of windsea is generally <10s,...

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At any location over the oceans, there is a spectrum of waves which describes how much wave energy is present for given wave frequencies and direction of propagation...

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These charts show the the wave energy flux (in kW m⁻¹) calculated as the integral, over all forecast wave frequencies and wave directions, of the product of the wave group speed and the two-dimensional energy wave spectrum...

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The height of topography above mean sea level and the depth of the sea for each model grid box ...

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The C3S Arctic Regional Reanalysis second generation (CARRA2) dataset contains daily and monthly meteorological variables at 2.5 km resolution. These variables are specified at single levels (including surface) and also at soil, height, pressure and model levels. These daily and monthly data are pre-calculated and have the following types depending on the variables: daily and monthly averages, extremes and totals.

calendar_today Interval/period: Tue, 10/01/1985 - Wed, 12/31/2025

The C3S Arctic Regional Reanalysis second generation (CARRA2) dataset contains 3-hourly analyses at 2.5 km resolution. These variables are specified at single levels (including surface) and also at soil, height, pressure and model levels. Additionally, hourly forecasts are available between the analysis times and particularly forecasts up to 18 hours initialised from the analyses at 00 and 12 UTC.

calendar_today Interval/period: Sun, 09/01/1985 - Wed, 12/31/2025

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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The ECMWF seasonal forecasts (SEAS5) are produced every month with a 51-member ensemble at ...

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This dataset provides meteorological and snow indicators for Europe, characterizing operating conditions of winter ski resorts under past and future climate scenarios. The dataset consists of 39 indicators of atmospheric and snow conditions computed in a similar manner for all mountain regions in Europe at the scale of NUTS-3 regions (Nomenclature of Territorial Units for Statistics) and by steps of 100 m elevation.

calendar_today Interval/period: Sun, 01/01/1950 - Fri, 01/01/2100

MUCAPE (Most Unstable Convective Available Potential Energy) is an indicator of atmospheric instability (the susceptibility of the troposphere to support free convection) and...

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This dataset provides hydrological seasonal reforecasts of monthly mean river discharge across Europe for the period 1993 to 2016. The first is an E-HYPE multi-model system comprising eight model realisations using a catchment-based resolution. The second comprises the E-HYPEgrid, VIC-WUR and LISFLOOD-EFAS hydrological models at a 5km gridded resolution.

calendar_today Interval/period: Fri, 01/01/2021 - Wed, 08/26/2026

These charts aim to point towards areas where anomalous weather is likely to occur. ...

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This chart shows 7-day mean anomalies for a range of parameters from the ECMWF Sub-seasonal ...

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This chart provides a range of skill scores relating to forecasts of the evolution of the sea ...

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This chart provides a range of skill scores relating to forecasts of the evolution of the sea ...

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**Note:** In **June 2023** ECMWF implemented a **major upgrade ...**

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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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Pangu-Weather: a deep learning-based system developed by Huawei. It is initialised with ECMWF analysis. Pangu-Weather operates at 0.25° resolution.

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Pangu-Weather: a deep learning-based system developed by Huawei. It is initialised with ECMWF analysis. Pangu-Weather operates at 0.25° resolution.

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Pangu-Weather: a deep learning-based system developed by Huawei. It is initialised with ECMWF analysis. Pangu-Weather operates at 0.25° resolution.

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This chart shows probability information regarding point precipitation, as derived from the ...

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850 hPa wet-bulb potential temperature is commonly used to identify air masses and a strong gradient of wet bulb potential temperature is indicative of fronts between two different air masses...

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