Syllabus

Syllabus#

Please read it carefully at the beginning of the class, and return to it as often as necessary.

Learning outcomes#

Upon successful completion of this unit, you will be able to:

  • Critically evaluate the current and future impacts of climate change using climate data (including observations and models).

  • Apply the necessary quantitative data manipulation skills to conduct climate impact analysis at both regional and global scales.

  • Analyse the interplay between hazard, exposure and vulnerability in the context of climate change risk assessment.

  • Appraise the significance of climate change adaptation planning and the broader societal implications of climate change across various regions and populations.

While quantifying climate risks includes quantifiying exposure, vulnerability, and hazard, the focus of this class will be on the physical impacts of climate change (hazards). We will not cover the social aspects of climate risks in great detail, but we will discuss them e.g. in the context of adaptation planning.

Parctical skills#

To reach the learning goals listed above, you will need to develop practical skills in climate science and programming. Specifically, this class will help you to:

  • Build Python programming skills tailored to climate science and risk assessment tasks.

  • Handle, process, and effectively visualize large climate datasets.

  • Analyze and interpret climate data to assess risks across sectors, regions, and time scales.

  • Apply statistical and computational tools to address real-world climate challenges.

Prerequisites#

This class is designed for master’s level students with a background in climate science and some prior exposure to programming. While no formal training in programming or Python is required, it is assumed that you have used a programming language (e.g., Python, Matlab, R) and are familiar with basic programming structures such as loops, functions, and conditional statements.

Organisation of the class#

The term is 10 weeks long, with a consolidation week half-term. Each week is organized as follows:

  • During the lectures (usually on Wednesdays), we will discuss the theoretical aspects of climate risks, and I will introduce you to the new concepts of this class.

  • During the workshops (usually on Thursdays), we will work together on practical exercises and coding problems. This is the time to ask questions and to get help with the exercises. You will always be informed one week in advance about the content of the next workshop. We will follow the flipped classroom model: you will acquire new knowledge at home by reading online materials and coding where appropriate. We will then use the time together in class to discuss the materials and check your code, projects, and understanding.

For the practical exercises, you will need a computer with an internet connection. You can work either on your own computer (laptop) or on the working stations in the computer room.

Each week, I will ask one group to present the assignment from the week before. Each of you will therefore have to present once. This is not marked, and is purely for me to check if the class is following, and if I need to adapt the pace of the lecture.

Assessment#

The assessment for this class will be an individual climate change risk assessment project. You will prepare a technical report that quantifies a physical hazard (e.g., floods, extreme events, heatwaves) and discusses its impacts on populations or ecosystems in a region and context of your choice. Detailed instructions for the assessment will be released in due course.

As a formative assessment (not marked), you will be asked to outline your project idea and plans, on which you will receive feedback from the instructor.

Weekly lesson plan#

It’s the first time I’m teaching this class, so the lesson plan is subject to change (I’ll update this page regularly). Here is the current plan:

Lecture schedule#

  • Lecture 1: Introduction to Climate Change and Risk

  • Lecture 2: Climate data

  • Lecture 3: Statistical methods for risk assessments

  • Lecture 4: Attribution of climate risks

  • Lecture 5: Sea level rise and coastal risks

  • Lecture 6: Quantifying Exposure and Vulnerability

  • Lecture 7: Adaptation to Reduce Climate Risks

The lecture slides are available on blackboard.

Workshop schedule#

  • Workshop 01: IPCC AR6 WG2 - Part 1

  • Workshop 02: IPCC AR6 WG2 - Part 2

  • Workshop 03: Getting started with Python and climate data analysis (Assignment: ERA5 data)

  • Workshop 04: More advanced tools for gridded climate data (Assignment: CMIP6 data)

  • Workshop 05: Timeseries analysis and extreme values (Assignment: timeseries analysis)

  • Workshop 06: Extreme value distribution (Assignment: ISIMIP timeseries)

  • Workshop 07: Glacier runoff

  • Workshop 08: Huricane Katrina risk assessment (Assignment: Hurricane Katrina analogue in 2100)