ECMWF | 23-27 March 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 will consider the challenge of making predictions from days to seasons ahead.
The predictability of the atmosphere in the medium and extended range will be considered, including different aspects of the Earth system which give rise to predictability on longer time scales. Elements of a probabilistic forecast system as well as its calibration and verification will be presented.
The course is a combination of lectures, hands-on practicals and group discussion sessions and will include some elements of pre-course study.
Please note that this course does not cover methodologies for downscaling/post-processing, probabilistic products or discuss decadal prediction.
- Theoretical ideas - chaos, predictability limits
- Ensemble methods - taking account of uncertainty in initial conditions and in the model
- Predictability in the extended range - ocean, sea-ice, stratosphere, land
- Probabilistic forecast initialisation, modelling, evaluation and verification
- ECMWF medium-range, monthly and seasonal systems.
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.