News Detail - September 2010

Following various requests for more training on data assimilation we are very pleased to offer a short intensive course at Surrey University.

NCEO 2 DAY INTENSIVE COURSE ON DATA ASSIMILATION

When: From 1400, Monday 5 July 2010 to 1530, Wednesday 7 July 2010

Where: University of Surrey, Guildford

Who should attend: Anyone in NCEO with an interest in learning more about data assimilation. We particularly encourage early career scientists (PhDs and PDRAs). Applications will be accepted on a first come first serve basis – 12 places are available on the course.

Costs: Accommodation, breakfast and lunches are provided free of charge. Participants will need to arrange and pay for their own transport and dinners on Monday and Tuesday...and of course beer money.

What is on offer: The course will be led by Ian Roulstone and Peter Jan van Leeuwen. An outline agenda is given below:

Monday:
1400 – 1600 Show and tell: participants describe their DA related work in 10 min.
This will allow talks on Tuesday and Wednesday to be tailored to participants’ needs.
1630 – 1730 Overview of data assimilation: from intuition to Bayes theorem and back
1730 Informal questions and answers, discussion....drinks....dinner....

Tuesday:
0900 - 1030 Variational methods: theory
1100 - 1300 Variational methods: exercises (using computer programs with guidance)
1400 – 1530 Ensemble methods: theory
1600 – 1800 Ensemble methods: exercises (using computer programs with guidance)
1800 Informal questions and answers, discussion.....drinks....dinner....

Wednesday:
0900 - 1030 Particle filters and other exotic stuff, an overview
1100 - 1230 Invited speakers on issues in real applications (former PhD students/postdocs)
1400 - 1530 What have you learned, feedback and establishing links for future informal collaboration/advise

How to apply: Please send an email to Zof Stott (zof.stott@nceo.ac.uk) marking you email DA Course. Please include your contact details and anything in particular you would like to see in the course.