This training course will be held at ECMWF in Reading (UK). We are constantly monitoring the COVID-19 travel situation and will adjust and adapt the format of the course if necessary.
This five-day course 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. An example timetable is shown for the online course in 2021 to give you some idea of what is covered.
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
This course will offer two levels of participation:
Level 1: Attend in person at ECMWF's headquarters to attend lessons & practical sessions. A course certificate will be issued.
Level 2: Remote access to lessons and opportunity to ask questions in a forum; no access to practical sessions. A course certificate will not be issued.
Please indicate on the registration form which level you are applying for.
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.