Analysis of Climate and Weather Data

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Course information

Course number 701-1253-00L
Time & Location Thursday 15.15-17.00 (CHN E42)
Lecturer C. Frei
Tutor Roman Attinger, IAC ETH Zurich

Course objectives

  • Introduce techniques of statistical data analysis used in modern 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.

Course schedule & notes

8 two-hour lectures & 5 supervised computer workshops.

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

Date Theme
22.09.16 1) Introduction, Basics & Exploratory Methods
29.09.16 Workshop: Introduction to R (Documents below)
06.10.16 2) Hypothesis Testing
13.10.16 3) Trend Analysis
20.10.16 Workshop: Basics & Trend Analysis (Documents below)
27.10.16 4) Extreme Value Analysis
03.11.16 Workshop: Extreme Value Analysis (Documents below)
10.11.16 No Lecture
17.11.16 5) Forecast Evaluation and Skill Scores (Part 1)
24.11.16 5) Forecast Evaluation and Skill Scores (Part 2)
01.12.16 Workshop: Forecast Evaluation and Skill Scores (Documents below)
08.12.16 6) Principal Component Analysis
15.12.16 6) Maximum Covariance Analysis
22.12.16 Workshop: PCA & MCA (Documents below)


Date Workshop Exercise Sheets:
29.09.2016 Workshop 0: Introduction to R demoR.R / R-Intro
20.10.2016 Workshop 1: Basics & Trend Analysis ex1.R
03.11.2016 Workshop 2 : Extreme Value Analysis ex2.R
01.12.2016 Workshop 3: Forecast Evaluation and Skill Scores ex3.R
22.12.2016 Workshop 4 : PCA & MCA ex4.R

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 R-project web-site.

An introduction to R for beginners will be given in a specific Workshop (01.10.2015). A detailed introduction is available from the R-project web-site.

For the time of the workshops a “fleet” of Macintosh Laptop Computers (Mac OS) will be available. Students are however encouraged to bring along their own portable computers (if available). We recommend you install R on your computer before the first workshop. The installation of the add-on packages needed for the ACWD workshops (see below) will also be explained during the workshop on 09.10.2014.

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:

  1. 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.
  2. 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., 2011: Statistical Methods in the Atmospheric Sciences. 3rd edition, Academic Press Inc., 704 pp. (Comprehensive text book from basic concepts to advanced techniques.)
  • 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.)
  • References to publications cited in the lecture notes.

Credit points & examination

Oral examination after the end of the semester (session examination, 30 minutes). 3 ECTS credits.

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