Academic year 2016/2017 Syllabus of previous years
Official course title CLIMATE MODELLING
Course code CM0450 (AF:212660 AR:97119)
Modality Frontal Lesson
ECTS credits 6
Degree level Master's Degree Programme (DM270)
Educational sector code SECS-S/01
Period 1st Semester
Course year 2
Course objectives
The course aims at providing students with an introduction to statistical analysis of climate time series. Important statistical methods including regression modelling, autocorrelation, smoothing and spectral analysis will be discussed and used to enhance data interpretation and answer scientific questions. Practicals with the R statistical software will be an integral part of the course.
Basic knowledge of statistics at the level of an introductory bachelor (Italian laurea triennale) course.
1. Climate time series
2. Regression models
3. Time series components
4. Exploratory methods for time series
5. Spectral analysis
6. Statistical models for climate time series
7. Applications and case studies
Referral texts
Pruscha, H. (2013). Statistical Analysis of Climate Series. Springer
Chandler, R. and Scott, M. (2011). Statistical Methods for Trend Detection and Analysis in the Environmental Sciences. Wiley
von Storch, H. and Zwiers, F.W. (1999). Statistical Analysis in Climate Research. Cambridge University Press
Type of exam
Teaching methods
Theoretical lectures complemented by exercise classes and lab sessions. Teaching material prepared by the lecturer will be distributed during the course. The statistical software used in the course is R (
Teaching language
Final examination will consist of two steps:
1) preparation of an individual report regarding the analysis of an assigned dataset;
2) oral illustration of the report.
  • Course with sustainable contents
  • University credits of sustainability: 6
  • Lecture notes, material for reference or for self-assessment available online or as e-book
  • Use of open-source software
Last update of the programme