DARC/NCEO Data Assimilation Training course, Univ. of Reading, 2022
Outline
Data assimilation is one of the core activities needed to deliver weather forecasts, and to help understand the environment. This course will provide an introduction to data assimilation methods used in numerical weather prediction, including some of the latest developments. All methods will be derived from a common framework to allow a full overview of their assumptions and applicability. Furthermore, participants will get the opportunity to apply data assimilation methods to small numerical models, in order to obtain hands-on experience with the different methods.
- When?
- Tuesday 21st – Friday 24th June 2022.
- Where?
- University of Reading, UK (Covid restrictions permitting; an on-line course will be offered if in-person lectures are not possible).
- A map of the campus is available here.
- Who is it for?
- This course is suitable for postgraduate students, post-doctoral researchers, and weather service employees who would like an introduction to, and a deeper understanding of, data assimilation.
- How will the course be delivered?
- The course will be a combination of lectures and computer practicals.
- What topics will be covered?
- Introduction to Data Assimilation
- Co-variances
- Variational Methods: Theory and practical issues
- Computer practicals Variational methods
- Ensemble Kalman Filter Methods: Theory and practical issues
- Computer practicals Ensemble Kalman filters
- Non-linear data assimilation and Particle Filters: Theory and practical issues
- Computer practicals Particle filters
- Hybrid Methods: Theory and practical issues
- Computer practicals Hybrid methods
- When to use which method
- What prerequisites are required?
- Some knowledge of basic calculus, statistics, and linear algebra. Mathematical primers are available below.
- Who will deliver the lectures?
- Lectures will be delivered by members of DARC including: Alison Fowler, Amos Lawless, Javier Amezcua, Ross Bannister, and Sarah Dance.
- How much will it cost to attend?
- The course is free to attend. Attendees will need to pay for their own travel, accommodation, and subsistence.
- How will I run the practicals?
- A PC and Python software will be provided. You may alternatively run the practicals on your own laptop computer.
- How do I apply?
- To apply for a place, please send an email to Uzma Saeed (u.saeed@reading.ac.uk), with a short description of your current research interests (around 50-100 words) by Tuesday 24th May 2022. Applications will be looked at as they arrive, until all the places have been allocated.
Supplementary Material
- Campus map (web page)
- Setting-up for the computer practicals (pdf)
- Practicals – variational and ensemble Kalman filter (zip)
- Practicals – hydrids (zip)
- Practicals – Bayes theorem and particle filters (zip)
- Maths primer (pdf)
- Useful linear algebra (pdf)
- Inner and outer products (pdf)
- Covariances (pdf)
- Basic statistical concepts (pdf)
- Notation (pdf)
- List of suggested references (pdf)
Course timetable and lecture/practical material
The course will be held in the Agriculture Building (Ag) on the main Whiteknights campus of the University of Reading (building 59 on the map). Registration and lectures will be in room 1L16 and practicals in the PC lab GL20.
Handouts will not be provided by the lecturers, but lectures can be downloaded via the on-line timetable below when they become available.
Information about the models used in the practicals
| Tuesday 21st June 2022 | |||||
| 09.00 | 09.30 | Ag 1L16 | Registration | ||
| 09.30 | 09.45 | “ | Welcome & introduction | ||
| 09.45 | 10.40 | “ | Lecture: Introduction to data assimilation | Amos Lawless | |
| 10.40 | 11.00 | Break | |||
| 11.00 | 12.00 | “ | Lecture: Variational data assimilation I | Ross Bannister | |
| 12.10 | 13:00 | “ | Lecture: Variational data assimilation II | Ross Bannister | |
| 13:05 | 14:00 | Lunch break | |||
| 14.00 | 16.00 | PC lab Ag GL20 | Practical: Variational data assimilation | github instructions |
|
| 16.00 | 16.20 | Break | |||
| 16.20 | 17.20 | Ag 1L16 | Lecture: Variational methods practicalities | Amos Lawless | |
| 17.30 | Maths common room, 112 (building 4) | Icebreaker reception | |||
| Wednesday 22nd June 2022 | |||||
| 09.00 | 10.00 | Ag 1L16 | Lecture: Ensemble Kalman filter I | Alison Fowler | |
| 10.10 | 11.10 | “ | Lecture: Ensemble Kalman filter II | Alison Fowler | |
| 11.10 | 11.40 | Break | |||
| 11.40 | 12.40 | “ | Lecture: Dynamical systems and data assimilation | Jochen Broecker | |
| 12.45 | 14.00 | Lunch break | |||
| 14.00 | 16.00 | PC lab Ag GL20 | Practical: EnKF | github (as above) instructions (as above) |
|
| 16.00 | 16.20 | Break | |||
| 16.20 | 17.20 | Ag 1L16 | Lecture: Applications lecture – Exploiting infrasound measurements | Javier Amezcua | |
| Thursday 23 rd June 2022 | |||||
| 09.00 | 10.00 | Ag 1L16 | Lecture: Hybrid methods I | Javier Amezcua | |
| 10.10 | 11.10 | “ | Lecture: Hybrid methods II | Javier Amezcua | |
| 11.20 | 11.40 | Break | |||
| 11.40 | 12.40 | “ | Lecture: Machine learning and data assimilation | Jochen Broecker | |
| 12.45 | 14.00 | Lunch break | |||
| 14.00 | 16.00 | PC lab Ag GL20 | Practical: Hybrid methods | github instructions (as above) |
|
| 16.00 | 16.20 | Break | |||
| 16.20 | 17.20 | Ag 1L16 | Lecture: Particle filters I | Peter Jan van Leeuwen | |
| Las Iguanas, Central Reading | Dinner – 19.00 | ||||
| Friday 24 th June 2022 | |||||
| 09.15 | 10.30 | Ag 1L16 | Lecture: Particle filters II | Peter Jan van Leeuwen | As above pdf |
| 10.30 | 11.00 | Break | |||
| 11.00 | 13.00 | PC lab Ag GL20 | Practical: Particle filters | github instructions (as above) |
|
| 13.00 | 14.00 | Lunch break | |||
| 14.00 | 15.00 | Ag 1L16 | Lecture: What to use when | Ross Bannister | |
| 15.00 | 15.15 | “ | Certificates and closing words | ||