Single prediction that uses

observations prior information about the Earth-system ECMWF's highest-resolution model

HRES Direct model output Products offers "High Frequency products"  

4 forecast runs per day (00/06/12/18) (see dissemination schedule for details) Hourly steps to step 90 for all four runs.

Not all post-processed Products are available at 06/18 runs or in hourly steps.

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The sub-seasonal products comprise ensembles of individual forecasts up to 46 days and post-processed products of average conditions (e.g. weekly averages) and the associated uncertainty.

The purchase of the "Basic Set" +72, +96, +120, +144, +168 hrs is a mandatory prerequisite for the purchase of time steps in the range 12 to 66 hours.

The following sub-sets are available from the sub-seasonal forecast (46 days):

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These seasonal data comprises ensembles of individual forecasts coupled to an ocean model and post-processed products of average conditions (e.g. monthly averages) with the associated uncertainty. Products are available for forecast month 8-13, each quarter (February, May, August, November).

The following sub-sets are available:

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ecCharts

This licence provides access to ECMWF interactive ecCharts tool to visualise analysis and forecast products  Please note that access to the ecCharts is for End User use only (internal).  

ECMWF ecCharts web service is available and we are pleased to be able to offer the service for evaluation to customers of ECMWF's web products.

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Ensemble forecast runs produced by the ECMWF Artificial Intelligence Forecasting System (AIFS) Ensemble model.

4 forecast runs per day (00/06/12/18) 6 hourly steps to 360 (15 days)

More information can be found on the implementation page. 

X-i: AIFS ENS forecast

Product description

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On 12 May 2026, a new forecast stream will be produced by ECMWF's operational Artificial Intelligence Forecasting System ensemble model (AIFS ENS).

The new forecast stream is for wave forecast runs, marking ECMWF's first operational data-driven wave forecasts.

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The Sub-seasonal To Seasonal dataset (S2S) consists of global ensemble real-time forecasts and reforecasts from thirteen numerical weather prediction (NWP) and research centres.
S2S project behind the dataset started in 2013 as a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP).
The goal of S2S project was to improve sub-seasonal forecast skill through combining multiple forecasting systems, enable multi-model evaluations and enhance knowledge sharing between operational centres.

calendar_today Interval/period: Thu, 01/01/2015 - Wed, 05/06/2026

The Sub-seasonal To Seasonal dataset (S2S) consists of global ensemble real-time forecasts and reforecasts from thirteen numerical weather prediction (NWP) and research centres.
S2S project behind the dataset started in 2013 as a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP).
The goal of S2S project was to improve sub-seasonal forecast skill through combining multiple forecasting systems, enable multi-model evaluations and enhance knowledge sharing between operational centres.

calendar_today Interval/period: Tue, 03/01/2011 - Tue, 06/09/2026

Single forecast runs produced by the ECMWF Artificial Intelligence Forecasting System (AIFS) deterministic model.

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On 12 May 2026, a new forecast stream will be produced by ECMWF's operational Artificial Intelligence Forecasting System deterministic model (AIFS Single).

The new forecast stream is for wave forecast runs, marking ECMWF's first operational data-driven wave forecasts.

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Ensemble (ENS) of forecasts providing an estimate of the reliability of a single forecast.

ENS offers  "High Frequency products"  until step 144:

4 daily runs: 00, 06, 12 and 18 UTC hourly until step 90 3-hourly from 93 to 144

Most Post-processed Products are not available at 06/18 runs or in hourly steps. An exception are Tropical Cycle tracks (set III-viii) which is available for all daily runs: 00, 06, 12 and 18 UTC.

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 CAMS Global atmospheric composition forecast production system is used to produce the daily forecasts of pollutants, aerosols and greenhouse gases across the globe. Satellite observations of atmospheric composition are merged with a detailed computer simulation of the atmosphere using a method called data assimilation. The resulting analyses, i.e.

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Products based on an ensemble of forecasts providing an estimate of the reliability of a single forecast.

The purchase of the "Basic Set" +72, +96, +120, +144, +168 hrs is a mandatory prerequisite for the purchase of time steps in the range 12 to 66 hours.

The following sub-sets are available from the ENS-WAM:

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HRES-WAM (High RESolution WAve Model) is coupled to the atmospheric model (HRES) and it is a Direct model output Products offers "High Frequency products":

4 forecast runs per day (00/06/12/18) (see dissemination schedule for details) Hourly steps to step 90 for all four runs

The  model computes between the latitudes -78 and 90, the output grid is artificially extended to -90.

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SEAS comprises ensembles of individual forecasts coupled to an ocean model and post-processed products of average conditions (e.g. monthly averages) with the associated uncertainty. Products are available up to 7 months ahead.

The following sub-sets are available:

V-i: Monthly means of ensemble means

Field computed from data of the daily individual forecast runs (section V-v) and averaged over all ensemble members. The fields are provided in GRIB code.

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The International Grand Global Ensemble (TIGGE) dataset consists of global medium-range ensemble forecasts from thirteen numerical weather prediction (NWP) centres.
The dataset has been available since October 2006. TIGGE was established as a key component of THORPEX: a World Weather Research Programme to accelerate the improvements in the accuracy of 1-day to 2 week high-impact weather forecasts (THORPEX stands for THe Observing system Research and Predictability EXperiment)

calendar_today Interval/period: Sun, 10/01/2006 - Wed, 05/06/2026