VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.
Analysis of Climate and Weather Data
Last Updated: 2026-06-03 00:07:40
Abstract
An introduction to methods of statistical data analysis in meteorology and climatology. Applications of hypothesis testing, extreme value analysis, evaluation of predictions, principal component analysis.Course goals: Participants understand the theoretical concepts and purpose of methods, can apply them independently, and know how to interpret results professionally.
Objective
Students understand the theoretical foundations and probabilistic concepts of advanced analysis tools in meteorology and climatology. They can conduct such analyses independently, and they develop an attitude of scrutiny and an awareness of uncertainty when interpreting results. Participants improve skills in understanding technical literature that uses modern statistical data analyses.
Content
The course introduces several advanced methods of statistical data analysis frequently used in meteorology and climatology. It introduces the thoretical background of the methods, illustrates their application with example datasets, and discusses complications from assumptions and uncertainties. Generally, the course shall empower students to conduct data analysis thoughtfully and to interprete results critically. Topics covered: exploratory methods, hypothesis testing, analysis of climate trends, measuring the skill of deterministic and probabilistic predictions, analysis of extremes, principal component analysis and maximum covariance analysis, detection and attribution. The course is divided into lectures and computer workshops. Hands-on experimentation with example data shall encourage students in the practical application of methods and train professional interpretation of results. R (a free software environment for statistical computing) will be used during the workshop. A short introduction into R will be provided during the course.
Resources
Lecture Notes
Documentation and supporting material:- slides used during the lecture- excercise sets and solutions- R-packages with software and example datasets for workshop sessionsAll material is made available via the lecture web-page.
Literature
For complementary reading: - Wilks D.S., 2011: Statistical Methods in the Atmospheric Science. (3rd edition). Academic Press Inc., Elsevier LTD (Oxford) - Coles S., 2001: An introduction to statistical modeling of extreme values. Springer, London. 208 pp.
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 90 minutes
- Aids
- handwritten summary, maximum 4 pages (2 sheets)
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture with exercise | Analysis of Climate and Weather Data | No time listed | 2 h weekly |
Offered In
-
-
Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed. All courses listed as core courses (not electives) for one of the following ETH MSc programmes, MSc Statistics, MSc Physics, MSc Computer Science, MSc (Applied) Mathematics, MSc Neural Systems and Computation, MSc Robotics, Systems, and Control, MSc Data Science, MSc Electrical Engineering and Information Technology, can be taken as an elective course in the MSc CSE without prior permission.)
-
-
-
-
Doctorate Environmental Systems Sciences (More Information at: )
-