This module will teach you about data sources, the role of satellite observations, satellite data measurements, assimilation, and monitoring of satellite observations.

All numerical weather prediction models have sources of uncertainty. In this lesson you will learn about these uncertainties and chaotic behaviour, why ensemble prediction is needed, and about ECMWF m...

Data assimilation is used in NWP to define ‘optimal' initial conditions for numerical forecasts. In this lesson you will define data assimilation and explore how it is used at ECMWF.

Sub-grid-scale processes are not explicitly simulated in NWP so must be parameterized. This lesson describes how the parameterization is done at ECMWF and the challenges faced.

This lesson describes the key microphysical processes of cloud and precipitation parametrization with a focus on warm-phase processes and how these are used in NWP.

ecFlow is a workflow package that enables users to run programmes behind a firewall. During this lesson you will learn ecFlow vocabulary and how to run a simple suite.

Metview is a powerful meteorological workstation application that enables you to access, process and visualise meteorological data. In this lesson you will learn how to use MetView.

This lesson looks at the three classes of parametrization schemes and the main characteristics of the IFS scheme.

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

This lesson describes the key microphysical processes for ice and mixed-phase cloud and precipitation in the atmosphere, and the uncertainties in parametrization.