Statistical methods in global climate change research
- Lecturers
- Elisabete Alberdi Celaya
- Aitor Ciarreta
- Roberto Fernández Martínez
- Thomas Kneib
- Dae-Jin Lee
- Cristina Pizarro Irizar
- Didier Swingedouw
- Ramin Yahyapour
- Ainhoa Zarraga
- Language
- English
- Workload
- 14 h attendance time
76 h self-study time and group work - Credits
- 3
- Schedule
- Sessions will take place from 14:00 to 15:30 Göttingen time on Fridays from 28th October till 9th December 2022
- Type of Examination
- Assignements for each sub-session
- Location
- online
- Number of students
- 45
- Registration
- Please fill in and submit the registration form till 1st October 2022
This online seminar aims to provide an in-depth insight into advanced statistical methods in global climate change research and how these methods can be applied.
It will focus on the following topics:
- Climate change data visualization
- Generalized regression models
- Time series analysis
- Spatial statistics
- Clustering techniques
- High-performance data analysis and
- Climate reconstruction and climate projections.
We invite PhD students who are working with statistical methods in the broad field of climate research as part of their dissertation.
The University of Göttingen is organising the seminar in cooperation with the University of the Basque Country and the University of Bordeaux within the ENLIGHT network. The seminar is a combination of an asynchronous lecture
series with a round table as a weekly synchronous, complementary format in which experts from the respective universities engage in a discussion with the doctoral researchers.
If you face technical issues using the registration form, please contact maira.rueter@uni-goettingen.de