Showing 13 - 24 of 37 results
Machine Learning for Operational Forecasters Webinar 3: Case Studies

Machine Learning for Operational Forecasters Webinar 3: Case Studies

This webinar presents a range of case studies comparing the AIFS Single v1 and AIFS ENS v1 models with ECMWF’s IFS and...
Machine Learning for Operational Forecasters Webinar 2: What you need to be aware of

Machine Learning for Operational Forecasters Webinar 2: What you need to be aware of

This webinar explores key considerations for operational forecasters when using forecasts produced by AIFS machine...
Machine Learning for Operational Forecasters Webinar 1: Discover Machine Learning Models

Machine Learning for Operational Forecasters Webinar 1: Discover Machine Learning Models

This webinar briefly describes ECMWF's machine learning work and models - AIFS Single v1 and AIFS ENS v1. How to access...
ECMWF IFS Cycle 50r1 webinar: Introduction to Cycle 50r1 - 15 September 2025

ECMWF IFS Cycle 50r1 webinar: Introduction to Cycle 50r1 - 15 September 2025

Format: Videos
ECMWF’s next scientific model upgrade at the Data Centre in Bologna will be IFS Cycle 50r1. 50r1 brings major changes to...
Discover Anemoi: Inference

Discover Anemoi: Inference

Format: Videos
After successfully training a model and saving it to disk, we can run the model in inference mode and obtain predictions...
Representing model uncertainty with stochastic physics

Representing model uncertainty with stochastic physics

Format: Interactive modules (eLearning)

Explore sources of uncertainty in NWP and how this is represented in the IFS using stochastic physics.

Satellite observations and their role in NWP

Satellite observations and their role in NWP

Format: Interactive modules (eLearning)

Learn about the role of satellite observations and measurements, and how these are assimilated and monitored for NWP.

Forecast Jumpiness: An introduction

Forecast Jumpiness: An introduction

Format: Interactive modules (eLearning)

Learn about the ways in which forecast jumpiness can appear and how it can be mitigated.

Sources of Uncertainty

Sources of Uncertainty

Format: Interactive modules (eLearning)

Learn about uncertainties and chaotic behaviour in NWP, why ensembles are needed and how they are used at ECMWF.

Parametrisation of diabatic processes - case studies (convection)

Parametrisation of diabatic processes - case studies (convection)

Format: Interactive modules (eLearning)

Four case studies exploring the conditions that cause deep convection, considering predictability and forecast errors.

An introduction to single-column modelling

An introduction to single-column modelling

Format: Interactive modules (eLearning)

How SCM is used to investigate the physical processes of a global model in isolation, its applications and limitations.

Parametrisation of diabatic processes - Convection in the context of large-scale circulation

Parametrisation of diabatic processes - Convection in the context of large-scale circulation

Format: Interactive modules (eLearning)

This lesson will take you through what convection is and the phenomena it causes.