Admission requirements
Required course(s):
Earth System Science
A 200-level or 300-level course in the Earth, Energy and Sustainability (EES) Major
Recommended course(s):
Quantitative Research Methods, or
Geographic Information Systems
Description
Numerical models play a crucial role in geoscience research and serve as valuable tools for engineers, natural resource managers, and policymakers. While General Circulation Models (GCMs) are most famous, due to their role in constructing future climate scenarios, there are numerous other Earth system models employed in various research areas, policy making processes, and infrastructure design. For instance, hydrologic models help determine the properties and locations of flood infrastructure in riverine and coastal regions, ice sheet models are used to predict future sea-level changes, and biogeochemical models aid in identifying potential harmful algal blooms. Having a fundamental understanding of Earth system modeling is vital for environmental scientists to effectively utilize and interpret model outputs.
However, the Earth is also a complex system that cannot easily be described by a set of linear relationships. For models to be informative, one requires a thorough understanding of these complex relations and the knowledge to translate them into a model framework
This course offers an introduction to the workings, pros, and cons of several Earth system models. Students will build simple Earth models themselves and work with model output in commonly used datasets. In the course, we will work through several models to study a hydroclimatic extreme event and its aftermath. Some examples of models that we will look at are Extreme Value Theory, GCM model output, and the HEC-RAS hydrologic model software.
Course Objectives
Content
At the end of the course students can:
Comprehensively characterize Earth system models and assess their quality.
Describe the basics of Extreme Value Theory, General Circulation Models, reanalysis data, and hydrologic models.
Describe how different types of models can be calibrated, validated and used for prediction.
Describe possible problems with capturing complex natural processes in a model, and the potential solutions.
Skills
At the end of the course students can:
Analyses different types of Earth system data
Build simple statical models of extreme events in R
Build simple hydrological models in HEC-RAS
Employ Earth system models to solve sustainability challenges
Timetable
Timetables for courses offered at Leiden University College in 2023-2024 will be published on this page of the e-Prospectus.
Mode of instruction
The main goal of this course is for students to become comfortable with building simple models in R or external software. Naturally the course will cover some theory regarding Earth system processes, but mostly we will work together to build simple models. Classes will start with lectures presenting the necessary background to study Earth system models. Next students will work (together) on computer exercises in which they apply the concepts from the lectures. Students will learn to apply Extreme Value Theory, reanalysis data and the HEC-RAS software to study an extreme event.
Throughout the course we will use the program language R. Student should be able to at least open an R script and run it.
Assessment Method
Participation (15%)
News Paper Assignment (10%)
Lab I: Sandbox (15%)
Lab II: Extreme Value Theory (15%)
Lab III: Climate Data (15%)
Group poster: Coupled Earth system models (30%)
Reading list
Book: Thinking in Systems: A Primer by Donella Meadows.
A reader with papers will be made available at the start of class.
Registration
Courses offered at Leiden University College (LUC) are usually only open to LUC students and LUC exchange students. Leiden University students who participate in one of the university’s Honours tracks or programmes may register for one LUC course, if availability permits. Registration is coordinated by the Education Coordinator, course.administration@luc.leidenuniv.nl.
Contact
Dr. Joeri Reinders, email j.b.reinders@luc.leidenuniv.nl
Remarks
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