Analysis of Climate and Weather Data

Introduce techniques of statistical data analysis used in climate sciences,
Empower students to conduct own analyses and to professionally interpret results in scientific literature,
Excerzise the application and interpretation with real data in computer workshops.

9 two-hour lectures & 5 supervised computer workshops.

Course notes (slides) are provided as pdfs in the table below.

Training sets (a catalogue of questions) are provided to consolidate the understanding of the topics of the lecture.

ATTENTION: There are no power sockets in the lecture room. Please bring your laptop charged for the workshops!

Computer workshops are based on the software "R environment for statistical computing and graphics" - short "R". R is platform independent and is freely available from the external page R-project web-site. Most people work with R using external page RStudio that provides a comfortable user interface and development environment.

A short tutorial on R for beginners will be given in a specific Workshop (see Workshop 0 above). A external page detailed introduction is available from the R-project web-site.

Students will work on their own portable computers during the workshops. We recommend you install R and RStudio (in this order) on your computer before the first workshop, so that technical assistance can be provided in Workshop 0 if needed. The installation of the add-on packages (see below) will also be explained during Workshop 0.

Additional Packages

Additional software and datasets are needed for the workshops. They are provided as add-on packages (adding functionality to the R standard installation). To make your R installation ready for the workshops follow these steps:

Install the packages fitdistrplus, maps, mapproj, mapdata from the R-website via the "Package Installer" command in R. These are contributed packages generally available from the R-website.
Download the packages listed below, depending on the operating system you are using. These packages are available specifically for this course. Make sure you download the files without unzipping. Store them on your disk. Finally install the packages into R using the "Package Installer - Local Source Package" command in your R. The order of installation should be the same as they are listed below. Once the installation is complete you can delete the downloaded files on your disk.

Packages for Linux and Mac

Packages for Windows

Wilks D.S., 2019: Statistical Methods in the Atmospheric Sciences. 4th edition, Elsevier, 818 pp. (Comprehensive text book from basic concepts to advanced techniques.) [external page link]
Coles, S., 2001: An introduction to statistical modeling of extreme values. Springer, London. 208 pp. (Specialized text book on principles and application of extreme value analysis.) [external page link]
protected page References to publications cited in the lecture notes.

Date: Mo 27.01.2025, 08:30-10:00

Room: ML D 28

Bring along your students card

Written examination after the end of the semester (session examination, 90 minutes, English)

Aids: 4-page (2 A4 sheets) hand-written summary

The questions of the exam are very close in style to those of the training sheets (see above). Multiple choice or short texts or brief calculations (mental). No programming

3 ECTS credits for passing the written exam (mark 4.0 or better).