Learn about sources of error in NWP, how they are quantified, and how ensembles are evaluated.
Learn how EFI, SOT and Model Climate are built and provide forecast guidance for extreme, or severe weather events.
Six modules introducing the main topics in machine learning in the context of weather and climate.
This lesson focuses on ECGATE - ECMWF's server allocated for users' tasks, from submitting jobs to correcting errors.
Learn about the ways in which forecast jumpiness can appear and how it can be mitigated.
Learn about sources of predictability, seasonal forecast skill and the ECMWF sub-seasonal forecasting system.
Learn about seasonal predictability, how numerical seasonal forecast models work and their outputs.
ecFlow is a workflow package that enables users to run a large number of programmes behind a firewall.
Metview is a meteorological workstation application that enables you to access and visualise meteorological data.
The SAPP system is the ECMWF's operational acquisition and pre-processing system for observations and other input data.
Learn about the main sources of uncertainty in weather forecasting and how they are addressed in early warning systems.
The Meteorological Archival and Retrieval System (MARS) enables access to ECMWF data. Explore its computing capability
