AIFS Blog

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Introducing the Anemoi training-ready version of ERA5

The Anemoi training-ready version of ERA5 is now openly available. This dataset provides a ready-to-use machine-learning-optimised subset of ERA5 data enabling efficient training of models.
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Representing ocean wind waves in ECMWF's AIFS

We present data-driven ocean wave modelling for the AIFS, introducing two methods for integrating waves alongside the atmosphere. This improves the wave forecast accuracy and advances machine-learning-based Earth system modelling.
AIFS blog card 2m temperature verification

Verifying 2 m temperature forecasts in wintertime anticyclonic conditions

We provide a conditional verification of two-metre temperature forecasts from the AIFS Single (ML-based deterministic forecasts) and IFS Control forecasts during the winter of 2024/25, focusing on synoptic weather patterns to better understand when and where differences in forecast skill emerge.
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Discover Anemoi: Kicking off our 2025 machine learning training

In January, we launched our 2025 machine learning training webinars called 'Discover Anemoi'. The webinar series introduces the features and usage of the Anemoi AI weather forecasting framework.
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A year in ML for weather forecasting

A tour of the year past and some previews of the year to come.
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First AIFS model weights are now open

We highlight that the first AIFS model weights are now available and explain how you can use them yourself.
Excerpt from Aurora ML-based forecast chart

Accuracy versus activity

Forecast performance is multifaceted. We discuss how accuracy and activity can be ‘competing’ attributes for ML-based deterministic forecasts.
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Run AI models yourself from ECMWF open data

Users can now run AI models themselves using ECMWF’s open data, opening new possibilities for research, education and application development.
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Enter the ensembles

We introduce a first version of an ensemble AIFS, explain how it works, show some early results and explain where you can view charts.
Excerpt from 7-day forecast of 10m wind speed and sea-level pressure using AIFS data-driven stretched grid approach.

Data-driven regional modelling

With colleagues from MET Norway, we describe our collaboration on regional modelling and outline Anemoi, our work towards an ML framework for data-driven weather forecasts.
Excerpt from AIFS forecast chart for rain and mean sea level pressure

It's rain(ing) data

We provide an update on the AIFS, including the addition of precipitation fields and open AIFS data for all.
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First update to the AIFS

We have introduced a new version of the AIFS that now runs at a horizontal resolution of 28 km (0.25°) and has an updated architecture. The new model version improves forecast scores, especially for surface variables, where resolution is crucial.
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A new ML model in the ECMWF web charts

With the introduction of a new machine learning (ML) model in our web charts, we discuss the interpretation of scores, the performance/realism dilemma for ML model developers, and how ensemble systems could help in this case.
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ECMWF unveils alpha version of new ML model

This blog introduces an important companion to the Integrated Forecasting System (IFS), the AIFS, our Artificial Intelligence/Integrated Forecasting System. It is one of three components of our new machine learning project.