Webinar Series: Machine Learning for operational forecasters

Online | 3-28 November 2025

This webinar series focuses on ECMWF machine learning models and what you might need to know as an operational forecaster to use their outputs effectively. The webinars will focus on ECMWF's AIFS Single and AIFS ENS models.

Webinars are aimed at operational forecasters from ECMWF Member and Co-operating States. Operational forecasters in National Meteorological Services and other organisations from around the world are welcome to join however some data and tools may not be available to forecasters from non-ECMWF Member and Co-operating States.

All webinars will be recorded and made available on YouTube afterwards

Dates are being confirmed for the webinars, please register your interest to receive infomation when the webinar dates and times are confirmed.


Webinars

Webinar 1 - Discover Machine Learning Models for Operational Forecasters

TBC November 2025

This webinar will briefly describe ECMWF's machine learning work and models - AIFS Single v1 and AIFS ENS v1. How to access the machine learning model forecast data and products using ecCharts and OpenCharts will be demonstrated. An overview of future plans for the models will be given.

Speaker: TBC (ECMWF)

[Link to register]

 

Webinar 2 - Case Studies

TBC November 2025

This webinar will detail a variety of case studies comparing AIFS Single v1 and AIFS ENS v1 models to ECMWF's IFS and other Machine Learning models. The case studies will be supported by model performance statistics and verification scores.

Speaker: TBC (ECMWF)

[Link to register]

 

Webinar 3 - What you need to be aware of when using ECMWF's Machine Learning models

TBC November 2025

This webinar will discuss what an operational forecaster needs to consider and be aware of when using forecasts produced by machine learning models and when looking at their verification scores. It will also describe known AIFS forecast issues.

Speaker: TBC (ECMWF)

[Link to register]

 

November 2025


Location: Online


Format: Series of 3 online webinars


Please register for all webinars of interest individually. Registration closes at 16:00 UTC two days before each webinar.