Training

Uncover how climate models work and how they can be evaluated. Differences between climate projections, predictions and scenarios are explained.

About climate projections, differences between climate models, and how to choose from climate projection data.

Six modules introducing the main topics in machine learning in the context of weather and climate.

Learn about sources of error in NWP, how they are quantified, and how ensembles are evaluated.

Learn how sub-grid-scale processes (not explicitly simulated in NWP), are parameterised and how challenges are overcome.

Metview is a meteorological workstation application that enables you to access and visualise meteorological data.

ecFlow is a workflow package that enables users to run a large number of programmes behind a firewall.

Five modules covering decision trees, deep learning, uncertainty and generative models, and physics-guided approaches.

Learn about the unique role of snow in forecasting, from short-range to seasonal time scales.

Learn about data assimilation and how it is used to define ‘optimal' initial conditions for NWP at ECMWF.

This lesson teaches users the basics of climate reanalysis. The lesson explains how reanalyses are made, an overview of global reanalyses datasets, and their strengths and limitations.

From analysis of the past to future projections Short online courseBecause you don't have to be a climate scientist to make climate data work for you! ...