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Analysis of Climate and Weather Data
Last Updated: 2026-02-05 16:15:43
Abstract
An introduction into methods of statistical data analysis in meteorology and climatology. Applications of hypothesis testing, extreme value analysis, evaluation of deterministic and probabilistic predictions, principal component analysis.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. 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.
Learning Materials (Links)
- Main link
- Analysis of Climate and Weather Data
General Information
- Language
- English
- Levels
- DR , MSC , NDS
- 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
This course will be offered in autumn semseter 2023 for the last time.
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2 h weekly |
Offered In
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General Electives (Students may choose General Electives from the entire course programme of ETH Zurich - with the following restrictions: courses that belong to the first or second year of a Bachelor curriculum at ETH Zurich as well as courses from GESS "Science in Perspective" are not eligible here. The following courses are explicitly recommended to physics students by their lecturers. (Courses in this list may be assigned to the category "General Electives" directly in myStudies. For the category assignment of other eligible courses keep the choice "no category" and take contact with the Study Administration ( ) after having received the credits.))
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MAS in Sustainable Water Resources (The Master of Advanced Studies in Sustainable Water Resources is a 12 month full time postgraduate diploma programme. The focus of the programme is on issues of sustainability and water resources in Latin America, with special attention given to the impacts of development and climate change on water resources. The programme combines multidisciplinary coursework with high level research. Sample research topics include: water quality, water quantity, water for agriculture, water for the environment, adaptation to climate change, and integrated water resource management. Language: English. Credit hours: 66 ECTS. For further information please visit: )
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Doctorate Environmental Sciences (More Information at: )
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