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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This dataset provides surface-level particulate matter (PM2.5 and PM10) concentrations derived from in situ low-cost sensor (LCS) measurements, produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) in the context of the Horizon Europe All Data for Green Deal project. This dataset differs from existing air quality datasets by combining crowdsourced observations with a robust correction framework, producing high-resolution, reference-aligned gridded products.

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This dataset provides a record of fuel characteristics at high spatiotemporal resolution: ~9km, daily.
The two main variable groups are fuel load and fuel moisture, both of which are further divided by live/dead and wood/foliage fractions.
The dataset combines state-of-the-art model data (ERA5-Land) with observations from multiple satellites and in-situ variables into a globally complete and consistent dataset.

calendar_today Interval/period: Wed, 01/01/2003 - Fri, 12/31/2021

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