UE Climate and environmental variability



What are the scientific issues associated with climate and environmental variability?

How is this variability manifested at global, regional and local scales?

What statistical tools can be used to describe it?

This course aims to address these questions through practical assignments on machines.

The objective here is for students to acquire:

- knowledge of climate and environmental sciences

- knowledge of statistical tools for describing climate and environmental variability

- skills in one or more data-processing languages (mainly R and/or Python)

 The teaching is based on:

  1. Practical assignments where climate and/or environmental issues will be addressed through the analysis of datasets. Three statistical themes will be addressed:
    1. Average patterns: application of descriptive statistics tools
    2. Probability of climate events, uncertainties: application of probabilistic statistics
    3. Trend analysis: correlation methods, detection of non-stationarities and uncertainties
  2. A project to be conducted over the duration of the module, in pairs and supervised by a teacher.
  3. Lectures by scientific experts in analysis of climate and environmental variability and statistical analysis of the associated data.

Assessment is based on:

- Practical assignments (coefficient of 0.75): assessment of the preparation in the form of multiple choice questions or reports on the practical assignments.

- Assessment of the student's individual project (coefficient of 1.25): written report and oral presentation.


For each course theme, students receive support helping them acquire the pre-requisites needed for the statistical analyses. Students have to work on these basics independently prior to the practical assignments.


skin.odf-2017:SKIN_ODF_CONTENT_COURSE_INFOS_LIEUX_TITLEGrenoble - Saint-Martin d'Hères