Physics Laboratory of Climatology and Atmospheric Physics
A.Y. 2025/2026
Learning objectives
The course aims at introducing students, by means of a monographic experience, to the most common issues that it is necessary
considering for the analysis of long series of meteorological data.
considering for the analysis of long series of meteorological data.
Expected learning outcomes
At the end of the course, students must be able to perform an analysis of long series of meteorological data. Specifically they must be
able to face the following issues:
·Data organization;
·Quality checks;
·Homogeneity checks and data homogenization;
·Time series analysis, with particular focus on spatial and temporal trends;
·Analysis of the physical mechanism that may have determined the observed trends.
able to face the following issues:
·Data organization;
·Quality checks;
·Homogeneity checks and data homogenization;
·Time series analysis, with particular focus on spatial and temporal trends;
·Analysis of the physical mechanism that may have determined the observed trends.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First semester
Course syllabus
The course involves an experience in the field of Meteorology/Climatology;
The choice of topic investigated may vary from year to year, also on the basis of students demand and preparation.
The proposed experience for the academic year 2025/26 will focus on future climate scenarios.
The choice of topic investigated may vary from year to year, also on the basis of students demand and preparation.
The proposed experience for the academic year 2025/26 will focus on future climate scenarios.
Prerequisites for admission
Basic knowledge of the structure and properties of the atmosphere;
Elementary statistical techniques for climate data analysis;
Previous programming experience (regardless of language).
Elementary statistical techniques for climate data analysis;
Previous programming experience (regardless of language).
Teaching methods
The proposed experiment aims to teach students how to carry out a data analysis activity independently.
After a few preliminary lessons, during which the topics to be investigated and the methods to be used will be presented, students will work independently to find the best solutions for analysing the proposed data. These solutions will then be discussed with the teaching staff and, if necessary, appropriately recalibrated and supplemented.
Activities will be carried out in small groups (2-3 students).
Attendance is compulsory.
After a few preliminary lessons, during which the topics to be investigated and the methods to be used will be presented, students will work independently to find the best solutions for analysing the proposed data. These solutions will then be discussed with the teaching staff and, if necessary, appropriately recalibrated and supplemented.
Activities will be carried out in small groups (2-3 students).
Attendance is compulsory.
Teaching Resources
Scientific articles and/or manuals that will be made available on the course website on the MyAriel platform at www.unimi.it
Assessment methods and Criteria
The examination consists of an oral presentation of the results obtained in which the problems addressed and the adopted methodologies will be discussed.
FIS/06 - PHYSICS OF THE EARTH AND OF THE CIRCUMTERRESTRIAL MEDIUM - University credits: 3
FIS/07 - APPLIED PHYSICS - University credits: 3
FIS/07 - APPLIED PHYSICS - University credits: 3
Laboratories: 48 hours
Lessons: 14 hours
Lessons: 14 hours
Professors:
Manara Veronica, Maugeri Maurizio
Educational website(s)
Professor(s)