ECMWF has taken the ensemble version of the Artificial Intelligence Forecasting System (AIFS) into operations today, 1 July 2025, to run side by side with the traditional physics-based Integrated Forecasting System (IFS) to advance numerical weather prediction.
The ensemble version, called AIFS ENS, is a collection of 51 different forecasts with slight variations at any given time to provide the full range of possible scenarios. It comes after the release of a first operational version which runs a single forecast at a time, called AIFS Single, at the end of February.
Despite the accuracy of the AIFS Single, there is much more value to users if they can access the full range of possible scenarios.
Major gains
The new ensemble model outperforms state-of-the-art physics-based models for many measures, including surface temperature, with gains of up to 20%. At the moment, it works at a lower resolution (31 km) than the physics-based ensemble system (9 km), which remains indispensable for high-resolution fields and coupled Earth-system processes.
ECMWF is therefore also exploring hybrid systems that leverage the strengths of both approaches.
The high-accuracy ensemble model complements the portfolio of ECMWF services by using the opportunities made available by machine learning (ML) and artificial intelligence (AI).
The AIFS ENS relies on physics-based data assimilation to generate the initial conditions. However, it can generate forecasts over 10 times faster than the physics-based forecasting system, while reducing energy consumption by approximately 1,000 times.
“Working with and for 35 nations”
The Director-General of ECMWF, Florence Rabier, emphasised the significance of the development for our Member and Co-operating States.
She said: “ECMWF has now created an operational collection of 51 different forecasts with slight variations for our Artificial Intelligence Forecasting System (AIFS), which is a significant achievement and complements our physics-based products. But importantly, it’s not only us who are innovating. We are also working with and for 35 nations to advance weather science to improve global predictions. The availability of the AIFS ENS in conjunction with other ECMWF services will positively impact how national weather and meteorological services in our 35 Member and Co-operating States and beyond will be able to make their predictions and contribute to a safer society.”
ECMWF’s Director of Research, Andy Brown, said: “This new milestone demonstrates our dedication to science-led innovations that are focused on delivering a machine learning forecasting model which pushes the boundaries of efficiency and accuracy, and it underscores our commitment to harnessing the power of machine learning for the weather forecasting community.”
ECMWF is leveraging the potential of what AI/ML can do for weather science with this latest model. This is part of its co-development of the award winning Anemoi framework with many of its Member States, which provides an open-source framework for training AI forecasting systems, including the AIFS.
ECMWF’s Director of Forecasts and Services, Florian Pappenberger, said: “We see the AIFS and IFS as complementary, and part of providing a range of products to our user community, who decide what best suits their needs. Making such a system operational means that it is openly available and comes with 24/7 support for our meteorological community. We will continue to engage with our Member States and our user community to ensure more and more parameters are added to suit their ongoing needs, and we will continue to enhance the model offered in line with how we push the capabilities of our physics-based system.”
Further information
More information on the implementation of the AIFS ENS is available, and the model has also been presented in a webinar. In addition, a series of AIFS blog posts can be accessed on our website, and AIFS ENS forecast charts are available on our charts page.
