ECMWF | 30 March 2020 to 3 April 2020
COVID-19 (coronavirus) update
17 March 2020
As the situation around COVID-19 (coronavirus) continues to evolve we understand you will have questions about its impact on ECMWF events. At this stage, no events have been cancelled and we hope all scheduled events will take place as planned.
We are monitoring the situation closely and will notify registered participants if we need to postpone an event or deliver it virtually rather than physically. Due to this uncertain situation, ECMWF recommends that participants ensure that any travel and accommodation arrangements are made with appropriate cancellation policies until further notice.
Thank you for your understanding; for the most up-to-date information, continue checking this webpage.
This five-day module is a combination of lectures, hands-on practicals using the Single Column Model, and group problem classes.
During the course each parametrized process is introduced and then discusses theory, modelling and verification over several sessions.
- General aspects of parametrization and their relation to systematic forecast errors
- Radiation in numerical weather prediction
- The parametrization of moist processes (convection and clouds)
- The planetary boundary layer
- Land surface processes
- Parametrization of subgrid-scale orographic effects
- The representation of physical processes in data assimilation
Participants will be expected to take up to 4 online modules before taking the course. This will provide introductory information on parametrization, convection, single column modelling and the metview interface that will be used in the practical sessions.
It is anticipated that this study will take around 4 hours depending on levels of prior knowledge.
Participants should have a good meteorological and mathematical background, and are expected to be familiar with the contents of standard meteorological and mathematical textbooks.
Introductory material not covered by the course can be found in our lecture note series.
Some practical experience in numerical weather prediction is an advantage.
All lectures will be given in English.