Earth-System Data Analysis

In this course, the students learn about the analysis of climate data stemming from 4-dimensional observations or climate models, i.e., gridded data in time and space.

- ability to transfer modeling concept to simple geoscientific problems
- ability to analyse 4-dimensional climate data

oral exam

mündliche Prüfung

Kendal McGuffie, Ann Henderson-Sellers: The Climate Modelling Primer, 4th Edition. Wiley-Blackwell, 456 pp.,2014.
Hartmann, Dennis L.: Global Physical Climatology. Elsevier, 2nd edition, 498 pp., 2016.

1. SWS: Observational methods and networks; measured and derived quantities; interpolation of data (gridding)
2. SWS: Text and binary (netCDF) file formats and visualization of 4-dimensional data
3. SWS: Reading and writing netCDF files in Python I
4. SWS: Reading and writing netCDF files in Python II
5. SWS: Analyzing the mean state (annual, seasonal, climatological); diagnosing heat transport
6. SWS: Detection of changes in the mean state (simple hyp. testing, t-test)
7. SWS: Temporal characteristics - spectral anaylsis
8. SWS: Spatial patterns I - correlation analysis
9. SWS: Spatial patterns II - eigenfunction
10. SWS: Climate modes; exercise North Atlantic Oscillation and ENSO
11. SWS: Tele-connections in the climate system (e.g. ENSO)
12. SWS: Data-model comparison I (ex. Re-Analysis period)
13. SWS: Data-model comparison II (exercise paleo application; Last Glacial Maximum)
14. SWS: Analysis of future projections (exercise comparison of mean states)

Programmierung mit Python