EES 3310/5310

Course Description

Printable Syllabus

This page contains an abbreviated outline of the syllabus. The full syllabus (printed and PDF) are the definitive sources of information and policy for this course, so you should read that carefully at the beginning of the term.

Course Description

Basic Info:


Jonathan Gilligan
Office: SC 5735 and on Zoom
Office Hours: Monday 10:10–11:00 AM in person, Wednesday 8:00–9:00 PM, or by appointment. You can find link to the Zoom office hour on Brightspace, under “Office Hours.”

Graduate Teaching Assistant

Bryce Belanger
Office: Stevenson 5703A
Office Hours: Thursday 9:00–11:00 AM, or by appointment


Class meetings: MWF 9:05–9:55, SC 1117
Lab: Mon. 1:25–4:15, Wilson 120

Catalog Description

EES 3310/5310 Global Climate Change Scientific principles and policy applications. Earth’s past; evidence of human impact; future climate change; and economic, social, and ecological consequences. Economic, technological, and public policy responses.


Prerequisite: one of 1030, 1080, 1510, 1510, CHEM 1601, ECON 1010, ES 1401 or PHYS 1501, 1601, 1901. [4] (MNS)

Essentially, the pre-requisite is there to ensure that you are comfortable with quantitative methods in natural or social science or engineering. I expect you to be comfortable with using algebra to solve problems and that you are familiar with basic statistics.

The course does not expect calculus or advanced math.

If you believe that you have these skills, but have not taken one of the pre-requisites, please see me and I will be happy to make an exception.

Repeat Credit

Repeat credit for 2110. Students who have earned credit for 2110 will earn only one credit hour for this course.

Narrative Description

This course will study earth’s climate and the way it has changed throughout our planet’s history. We will study:

  • Determinants of climate: What factors affect climate, how do we know this, and how certain are we?
  • Scientific evidence about past climates: What do we know, how do we know it, and how certain are we?
  • Natural climate change in earth’s history.
  • Effects of human activity on global climate in the last 200 years.
  • What do we know about future climate change and how will it affect the quality of people’s lives?
  • How do economists and political scientists assess the costs of climate change and the value of policies to limit it?
  • What can we do to mitigate future global climate change or adapt to life in a different climate?
  • What is happening politically, both in the U.S. and internationally, to respond to climate change?

Goals for the Course

My goals for this course are that at the end of the semester:

  • You will have a solid quantitative understanding of the basic physical and chemical principles that control the system and be able to apply that knowledge to reasoning about the climate system and its response to disturbances.
  • You will have working familiarity with a variety of computer models that simulate various aspects of the climate system and be able to use those models to explore the implications of scientific principles that are too complex to calculate with pencil and paper.
  • You will have a solid scientific understanding of what scientists know, what they don’t know, and how they know what they know about how climate works, how and why it has changed in the past, and how it may change in the future.
  • You will be able to evaluate the evidence for and against the idea that human activity is warming the planet and assess for yourself whether the evidence is persuasive.
  • You will be familiar with the ways economists and policy analysts approach the problem of climate change and public policies that respond to it.
  • You will understand the history of scientific and political concern and activity around global warming, the principal policy measures being considered to address climate change, and their major strengths and weaknesses.
  • You will have the tools and knowledge to make informed decisions about what climate policies you support or oppose.
  • In the laboratory, you will learn to:
    • Use simple climate models to explore the dynamics of the climate system.
    • Use open-source statistical tools to download and analyze real climate data.
    • Follow established reproducible research practices.

When you leave this course, you will not be qualified to work as a climate scientist, but you will be able to follow and critically evaluate news reporting about climate change and climate policy, debate intelligently and knowledgeably, and be an informed voter.

I do not care whether you agree with me politically. I respect people who think for themselves. What counts is whether you can present your own position clearly and support it with solid evidence and reasoned argument.

Structure of the Course:

I divide the semester into two parts:

  1. Scientific Principles of Climate: For the first half of the semester, we will focus on the scientific principles of climate and natural climate change in earth’s past. This will be very mathematical, using basic algebra. We do not use calculus or other advanced math in this class, but you should be comfortable with simple algebraic equations. We will then look at climate change in the last two centuries and what might happen over the next several centuries. We will emphasize examining the scientific evidence to understand what it can and cannot tell us.
  2. Human Dimensions of Climate Change: Politics, Economics, etc.: For the second half of the semester, we will focus on the political, economic, and social aspects of climate change and possible public policy and technological responses.


The laboratory section of this course is very important. In the first half of the semester, you will use interactive computer models of the climate system to explore the implications of principles that we cover in class and in the reading, practice downloading and analyzing real climate data, and learning about best practices for reproducible research in order to make your work reliable, reproducible, and trustworthy.

In the second half, you will use computational tools to explore the challenges of replacing fossil fuels with clean energy (renewable or nuclear), conduct quantitative economic analyses of different kinds of climate policies, and engage in role-playing exercises to simulate the way different climate policies work in practice.

To make the laboratory sessions effective, it is essential that you show up on time and prepared for the labs.

Mr. Belanger and Prof. Gilligan will both have office hours when you can drop in and discuss the laboratories, and I recommend that you take advantage of our office hours to get help if you have difficulty with any part of the lab.

I recommend that you read all of the reading material for the lab before you come to lab. You will get much more out of the labs if you are prepared.

Reading Material

There are three required textbooks and one recommended book. I will also assign supplementary reading on the Internet or in handouts during the term and I will post these on Brightspace.

Required Textbooks:

There is a companion web site to Global Warming: Understanding the Forecast at , which includes interactive online computer models that we will use for some exercises in the book.

Optional Textbook:

  • Garett Grolemund and Hadley Wickham, R for Data Science , (O’Reilly 2017) ISBN: 978-1491910399 . This book gives a great introduction to using R for analyzing data, aimed at newcomers and beginners. The book is available in print, but you can also read the whole thing online for free at

    You do not need to read this book, but it may be very helpful as you are learning R. It focuses on explaining how to use the “tidyverse” group of R tools that we will be using extensively in lab.

Overview of Reading Materials

I will give out detailed reading that give specific pages to read for each class and notes on important things you should understand. I expect you to complete the reading before you come to class on the day for which the reading is assigned, so you can participate in discussions of the assigned material and ask questions if there are things you don’t understand.

While science aims to give correct answers to scientific questions, there are not right or wrong answers to questions of what is the best economic model with which to assess the costs of climate change or the best policy with which to respond to climate change, so I have chosen books and other reading material that present different points of view on the political and economic aspects.

Class Web Site

In addition to the Brightspace web site, I have set up a server at , where I post the web versions of class slides and interactive web-based applications to that can be useful for working with data output from agent-based modeling experiments.

Computer Software

For the laboratory, we will use four principal software tools:

  • R is a powerful tool for statistical analysis.

  • RStudio provides an interactive environment for working with R. Using RStudio makes R much more user-friendly and easy to work with.

  • git is a tool that helps you manage your work by keeping track of the changes you make as you write and edit text and analysis code, and it also helps you easily back up your work and synchronize it across multiple computers, including coordinating working together with a partner.

    git integrates into RStudio, which makes it easier to use.

    We will also use a web-based service called GitHub , which lets you easily save your work in the cloud (useful for backing it up in case something happens to your computer). GitHub is free for open-source software projects, and students can also get a free account for class work and personal projects.

  • LaTeX is a powerful typesetting tool. You won’t use this directly, but RMarkdown uses it behind the scenes to produce PDF documents. RMarkdown also allows you to produce web pages, and Word documents so using LaTeX will be optional for this course.

Details about the software and how to install it are included in the documentation for the first laboratory session.

Part of the assignment for the first lab is to install the necessary software (R , RStudio , and git ) on your computer before the first lab, so please read the lab instructions and get an early start on this.


Overview of reading assignments

I will give out detailed reading that give specific pages to read for each class and notes on important things you should understand. I expect you to complete the reading before you come to class on the day for which the reading is assigned, so you can participate in discussions of the assigned material and ask questions if there are things you don’t understand.

Lab Assignments

Lab assignments have two parts: First, there will be reading and sometimes some simple exercises or activities to do before you come to lab and then there will be a write-up due after the lab (typically, it will be due on the Monday morning one week after your lab session).

The instructions for the lab will be posted on the class web site a week before the lab, and an assignment will be posted on GitHub . The instructions explain the lab and tell you how to prepare for it. The assignment tells you what to do and provides an RMarkdown template for your write-up.

Basis for Grading

Class participation 5%
Midterm exam 10%
Laboratory 55%
Final Exam 30%

Tests and Examinations

The midterm exam will be a take-home test. You will submit it on Brightspace and it will be due on Thursday Mar 3 . The midterm will cover your knowledge of the basic science of the climate system and climate change.

The final exam will be an open-book take-home essay exam, for which you may use your books and notes. You will submit your take-home final electronically on Brightspace . The final exam is due by the end of the scheduled alternate final exam, at Saturday May. 7 at 11:00 am .

The final exam will be cumulative over all the material covered during the term.

Honor Code:

This course, like all courses at Vanderbilt, is conducted under the Honor Code.

  • Studying: As you study for this class, I encourage you to to seek help from me , from Mr. Belanger , or from other classmates or friends.

  • Lab Assignments: I encourage working together, and in most lab assignments you will be explicitly told to work with a partner. I also encourage you to talk with other classmates, as well as friends and acquaintances outside of class. You may discuss assignments, compare notes on how you are working a problem, and you may look at your classmates’ work on homework assignments. But you must work through the problems yourself in the work you turn in: Even if you have discussed the solution with others you must work through the steps yourself and express the answers in your own words. You may not simply copy someone else’s answer.

  • Tests and Exams: Tests are different from homework and labs: all work on tests and exams must be entirely your own. You may not work together with anyone or receive any help from anyone but me or from Mr. Belanger on exams and tests (this includes the take-home final exam).

If you ever have questions about how the Honor Code applies to your work in this course, please ask me or Mr. Belanger . Uncertainty about the Honor Code does not excuse a violation.

Research Integrity

Beyond the University Honor Code, this course also emphasizes the scientific ethical principles of research integrity. Honesty is a very important part of research integrity, but it is only one part. Clearly, science cannot work if scientists are not scrupulously honest about the results of their research and there is no tolerance for scientists who lie. But research integrity goes much farther. Real science happens in the context of a scientific community and the integrity of this community is critical. The ethical principles of research integrity have grown over the centuries to protect the integrity of the scientific community. Indeed, the mathematician and poet Jacob Bronowski wrote, in his book, Science and Human Values (Harper & Row, 1956) that what makes science work and makes it great is much less about the intellectual brilliance and skills of individual scientists than about the ethical commitment to truth and human dignity by the community of scientists.

Science does not proceed only by making leaps of discovery but also by making useful mistakes and then discovering and correcting the errors in those mistakes. Because of this, scientific integrity requires scientists to be extremely transparent and forthcoming about all the details of their research. It is not enough to sincerely report a discovery or an idea in good faith, but one must also provide others with the tools to critically examine that discovery and idea, and if a scientist learns, even many years later, that a report or discovery contained an error, they must correct the error and actively inform other scientists about it.

When a scientist discovers an error in their past work and does not promptly and actively correct it, other scientists may continue to rely on the truth of that result and thus waste time, effort, and money. Thus, both making one’s own work available to others so they can have the opportunity to find errors, and also to promptly and publicly report any errors that one finds in one’s own work are two critical pieces of research integrity.

Another aspect also involves the communal nature of science: None of us works in isolation, and every scientist’s work builds on work by others. There are two reasons why it is critical to acknowledge the role of others’ work in our own research reports: First, it is important to give others the credit for their contributions to our shared body of scientific knowledge. Secondly, it is important for others to know where the data and methods we use come from. If I use someone else’s data or methods for an analysis and it later turns out that there were problems with their data or methods, then it is important for people reading my work to be able to examine my work and evaluate how those errors might affect my own results.

I want to emphasize that these considerations about research integrity are not just negative things. They are very positive, which is why so many researchers are embracing them. By being transparent and forthcoming, and by encouraging others to reproduce your research results, you can enhance your reputation, both for honesty (you show that you have nothing to hide) and for being a good citizen of the scientific community by making it easy for other researchers to learn from your work and build on it to make new discoveries and build new and more powerful tools for analyzing data.

Where this is relevant to this course on Global Climate Change is in our practice of reproducible research in the laboratory portion of the course. Making our work, however humble, fully open and transparent so that others may examine it, criticize it, or build on it to develop new tools and make new discoveries is an essential part of research integrity.

In your lab reports it will be important for you to document where the data you worked with comes from (this will mostly be clearly spelled out in the assignments) and what methods you used to analyze it. Using the tools of R and RMarkdown will make it easy to almost automatically include this kind of transparency in your reports. As you do this throughout this course, you will learn the best practices adopted by the scientific community and develop habits of openness, transparency, and reproducibility for any research you do in the future in any area of society, whether in science, journalism, business, or other endeavors.

Final Note:

I have made every effort to plan a busy, exciting, and instructive semester. I may find during the term that I need to revise the syllabus to give more time to some subjects or to pass more quickly over others rather than covering them in depth. Thus, while I will attempt to follow this syllabus as closely as I can, you should realize that it is subject to change during the semester.