Data Assimilation and Visualization in Environmental Sciences
Advanced Training Course in Data assimilation and visualization in environmental sciences
University of Reading, 15 - 19 September 2014
Fully-funded places are available for a NERC-funded advanced training course in Data assimilation and visualization in environmental sciences, to be held in the School of Mathematical and Physical Sciences at the University of Reading, 15 -19 September 2014. The course will be delivered by scientists from the Data Assimilation Research Centre (DARC) from the University of Reading. The course is aimed at PhD students and early career researchers who are working in application areas and who wish to use data-assimilation and visualization techniques as part of their work.
In this course we will lead students through the science of data assimilation by means of both lectures on the theory of data assimilation and computer practicals, and give them experience in methods for visualizing the resulting large data sets. The course will take place over 5 days and will cover the following topics:
- Introduction to the basics of data assimilation;
- variational data assimilation;
- ensemble Kalman filters and hybrid methods;
- particle filters and Markov Chain Monte-Carlo methods;
- data visualization.
For each topic there will be a combination of lectures and computer-based exercises. As part of the computing practical element students will gain experience of running code on the national supercomputer Archer using the EMPIRE data-assimilation framework. Students will also be exposed to the latest in data visualization with the University of Reading's recently-installed video wall.
By the end of the course students will:
- Have an understanding of the mathematical principles behind common data assimilation methods.
- Have an understanding as to how they would implement data-assimilation methods for a real system.
- Have experience of running data-assimilation experiments with simplified and state-of-the-art models, using both a PC environment and the national supercomputer, and know how to interpret the results.
- Know different techniques for visualizing large data sets.
Funding and application procedure
A total of 30 fully-funded places are available. Funds will cover 5 nights' accommodation from Sunday 14 September to Thursday 18 September and meals from Sunday evening to Friday lunchtime, including the workshop dinner on Thursday evening. We will also provide a contribution towards travel expenses.
To apply for a place on the course please complete the application form below and email it to Dr Amos Lawless, email@example.com. Any queries about the course can be addressed to Amos Lawless on the same email.
Further information about data assimilation at the University of Reading can be found at the following link: