A subset of ECMWF real-time forecast data from the IFS and AIFS models is made available to the public free of charge. Their use is governed by the Creative Commons CC-BY-4.0 licence and the ECMWF Terms of Use.

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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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These products are available to the African Center of Meteorological Application for Development (ACMAD) countries.

Based on HRES

The products outlined below are disseminated via EUMETCast

Please refer to WMO Additional products  for the equivalent products available on a global domain via the ECMWF's DCPC FTP server.

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ECMWF has adopted an open data policy, with the objective of expanding free and equitable access to high‑quality numerical weather prediction data for the global meteorological community. This shift supports the socio‑economic benefits of weather and climate information and aligns with WMO policies on international data exchange and capacity development for National Meteorological and Hydrological Services (NMHSs).

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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 - Mon, 06/29/2026

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 - Sun, 08/09/2026

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 - Mon, 06/29/2026