- Docente: Alberto Montanari
- Credits: 3
- Language: English
- Moduli: Alberto Montanari (Modulo 1) (Modulo 2)
- Teaching Mode: Traditional lectures (Modulo 1) Traditional lectures (Modulo 2)
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Civil Engineering (cod. 8895)
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from Sep 25, 2025 to Oct 16, 2025
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from Oct 23, 2025 to Nov 06, 2025
Learning outcomes
Students will learn how to obtain publicly available past and future climatic scenarios, test their validity with the support of data visualization and make their evidence-based assessment for uncertainty estimation. Open source software will be used to download and analyse the output from global climate models, downscale the data at local spatial scale and fine time scale, detect climate change and its spatial variability. Several climatic variables will be considered by focusing on their physical and statistical behaviours and the reliability of their simulations.
Course contents
The course will focus on applied methods for generating future climate scenarios, to support load estimation for structures and infrastructure in the presence of climate change.
The teacher will make extensive use of interaction with students. For example, students will be given the optional opportunity of delivering presentations to the class and the public, developing software, preparing open source contributions. Students may propose additional ideas for interaction.
Lectures will be recorded and made freely available on the web. Tutorial documents will be provided in the form of open web pages under CC license, and therefore may be freely re-used by students. Tutorial are already available on the web site of the teacher.
Lectures include: (1) retrieval of open source climate scenarios. (2) Practical generation of future climate scenarios through climate models and stochastic models. (3) Technical estimation of extremes under climate change. (4) Technical evaluation of additional forcings induced by climate change.
Part of the course will be delivered online to propose to the students an innovative and web based approach to education.
Programming languages are R and Python.
Readings/Bibliography
The teacher will prepare dynamic documents to support the learning process, which will be made available in the form of an open e-book, which may be open to interactive contribution by students.
Teaching methods
The course is taught through lectures. These lectures will be developed at the computer, using the R and Python programming languages.
Assessment methods
The preparation of the student will be assessed through the discussion of a project exercise. A brief oral interview may follow.
The exam is passed if the student proves to be prepared on the exercises that were taught during the lectures. The teacher will explicitly mention to students during the lectures what are the basic requirements to pass the exam. The speaking capability will also be evaluated. The laude is reserved to students who are excellently prepared and prove to have integrated their preparation with personal in-depth analysis.
Teaching tools
The teacher will made available notes on his personal web-site. Scientific papers will be distributed during the lectures as well as summaries of recent research outcomes.
Lectures will be delivered with the physical presence of the teacher and will also be made available via online streaming.
Moreover, the teacher makes available videos of the lectures
Links to further information
https://www.albertomontanari.it
Office hours
See the website of Alberto Montanari
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