Special Math Lecture (Introduction to data assimilation)

Goals of the Course

Data assimilation plays a very important role in several fields of research, and has numerous applications. Our goal is to provide the necessary background information for understanding the underlying ideas and concepts. Applications will also be presented. The presentation will be accessible to all students, independently of their major.

Objectives of the Course

Provide the necessary foundations for a good understanding of the key ideas of data assimilation, and provide tools for successful applications of data assimilation techniques to specific problems.

Course Content

1. Motivation
2. Mathematical background
3. Basic algorithms of data assimilation
4. Variants and extensions of the Kalman filter

Course Prerequisites and Related Courses

Basic knowledge on calculus and linear algebra, as provided in Calculus I & II and in Linear algebra I & II. Motivated 1st year students can also attend without these prerequisites but after a discussion with the instructor.

Course Evaluation Method and Criteria

The final grade will be based on the active participation during the lectures and on some written reports. Students will be encouraged to work on applications related to their major during the semester. Students need to notify the course withdrawal to the instructor when they have no intention of finishing the course during the semester.

Textbook

Lecture Notes

Additional information

Reference Website

This lecture is provided under Creative Commons Attribution-Non Commercial-ShareAlike 4.0 International.

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