A ATM 623 Climate Modeling

Syllabus, Spring 2017

Course number: 9735 (3 credits)

Meets Tuesday, Thursday 1:15 - 2:35 AM in ES 328

Instructor: Brian Rose

Course website:



A-E, 3 credit, based on

  • Participation: 15%
  • Assignments: 55%
  • Final project: 30% (written report = 25%, oral presentation = 5%)

Prerequisites: permission of instructor

The course will assume some exposure to geophysical fluid dynamics and climate dynamics at first-year graduate level. Some coding experience in a high-level programming language (Python, Matlab, R, NCL, etc.) is necessary.

Course description and objectives

The focus of this course will be hands-on investigation of the climate system using numerical and mathematical models. We will collectively get our hands on a range of models, including both comprehensive GCMs and assorted simpler process models. We will use these models to build our understanding of topics such as

  • The global energy budget
  • The greenhouse effect and radiative-convective equilibrium
  • Radiative forcing and climate feedback analysis
  • Orbital geometry, insolation, and the ice ages
  • Arctic sea ice and its coupling to the global climate system
  • Mechanisms of heat transport in the atmosphere and ocean
  • Links between tropical precipitation and global energy flows.
  • Ocean heat uptake and storage

The topics are subject to change and may be adapted to students’ interests.

Course requirements:

  • Attendance and participation during in-class exercises
  • A computer with internet access and a scientific Python environment
  • Strongly recommended: a personal laptop computer with Anaconda Python
  • Occasional short presentations or leading class discussions on selected topics
  • Completion of regular assignments and final independent project

Reading and textbooks:

The principal source will be my own lecture notes, which I will distribute to the class. I will sometimes assign readings from papers and books. You may find this book useful (a copy will be on reserve at the Science Library):

K. McGuffie and A. Henderson-Sellers (2014), The Climate Modelling Primer (4th edition), Wiley Blackwell.

Attendance and participation policy:

A significant portion of the course grade is given for class participation. You are expected to attend all lectures and participate fully in class discussions and exercises. Any absence should be discussed with Prof. Rose in advance whenever possible (email preferred)


Much of the course will consist of hands-on computing exercises using the Python language. I will provide code to get us started on each problem. You need a Python environment installed on your computer. I strongly recommend Anaconda: the standard, comprehensive Python distribution for scientific computing. It will let you install everything you need quickly and easily, and is completely free.

The goal of the exercises is to carry out meaningful calculations. Grading will be based more on scientific understanding than on programming skill. Assignments will usually be letter-graded on a qualitative A-E scale, where A=excellent, B=good, C=fair, D=poor, E=fail.

Assignments will normally be due by the beginning of class on the stated due-date. Extensions will usually be granted for legitimate reasons but must be discussed in advance with Prof. Rose. Electronic submission of homework by email is preferred whenever possible.

Final project:

Each student will complete an independent research project exploring an issue in climate science and climate modeling. The project must include some original calculations described and carried out by you, as well as references to the peer-reviewed scientific literature. A written report and oral presentation are required. You will submit a project proposal (less than one page) by Friday March 10. You are encouraged to discuss your ideas with the instructor beforehand.

Your written report should be roughly 5 to 10 pages in length, and should follow standard formats for scientific papers (e.g. abstract, introduction, literature review, description of your calculations, results summarized in graphs etc., discussion of results including their shortcomings, conclusions). Grades for the written papers will be determined by both scientific content and clarity of presentation. Reports are due Friday May 12 2017.

Presentations will be scheduled for Thursday May 4 and Tuesday May 9 (the last two class days). Each student will give a 10-minute presentation, followed by a brief class discussion. The purpose of the oral presentations is to share your work with your classmates and practice your presentation skills. Grades for the oral presentation will be based primarily on clarity.

Academic integrity:

In this class we will strive to be interactive, learning by doing and by discussion. Some collaboration on exercises is therefore encouraged. However you are ultimately expected to submit your own work and your own thoughts, and to give proper credit to others for previous work and ideas.

This is very important when writing computer code! There is nothing wrong with borrowing useful pieces of code from classmates or online sources -- that is in fact the central principle of open-source software. However, you must always acknowledge the original author(s). You must also, wherever practical, understand the code you are borrowing and be able to explain what it does.

It is every student's responsibility to become familiar with the standards of academic integrity at UAlbany. Claims of ignorance, of unintentional error, or of academic or personal pressures are not sufficient reasons for violations of academic integrity. Please refer to the UAlbany academic integrity policies here: http://www.albany.edu/graduatebulletin/requirements_degree.htm#standards_integrity