Learn about seasonal predictability, how numerical seasonal forecast models work and their outputs.
Learn about uncertainties and chaotic behaviour in NWP, why ensembles are needed and how they are used at ECMWF.
Learn about data assimilation and how it is used to define ‘optimal' initial conditions for NWP at ECMWF.
Learn how sub-grid-scale processes (not explicitly simulated in NWP), are parameterised and how challenges are overcome.
Explore the key microphysical and warm-phase processes of cloud and precipitation parametrisation and their use in NWP.
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.
Six modules giving ML applications in observations, forecasting, data assimilation, post-processing, ocean and more.
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
This lesson describes the web services used to visualise geographical data and outlines what OGC and INSPIRE are.
