Learn about seasonal predictability, how numerical seasonal forecast models work and their outputs.
Learn about the role of satellite observations and measurements, and how these are assimilated and monitored for NWP.
Explore sources of uncertainty in NWP and how this is represented in the IFS using stochastic physics.
Learn about sources of predictability, seasonal forecast skill and the ECMWF sub-seasonal forecasting system.
Learn about the ways in which forecast jumpiness can appear and how it can be mitigated.
This lesson focuses on ECGATE - ECMWF's server allocated for users' tasks, from submitting jobs to correcting errors.
Learn about the unique role of snow in forecasting, from short-range to seasonal time scales.
Four case studies exploring the conditions that cause deep convection, considering predictability and forecast errors.
The Meteorological Archival and Retrieval System (MARS) enables users to access and retrieve ECMWF’s historical data.
How SCM is used to investigate the physical processes of a global model in isolation, its applications and limitations.
This lesson provides an overview of Metview's main features to analyse and edit input data for the single-column model.
This lesson describes the web services used to visualise geographical data and outlines what OGC and INSPIRE are.
