Quantitative Models of Climate-Sensitive Natural and Human Systems

GR5401 Quantitative Models of Climate-Sensitive Natural and Human Systems

This course provides the fundamentals needed for analyzing climate datasets and the basics of decision making under uncertain climate conditions.

Credit hours: 4

Semester: Fall

Instructors: Simon Mason and Mingfang Ting

Course Objective:

The objective of this course is to provide students with quantitative skills in analyzing climate data, understanding statistical methods of making climate forecasts, as well as using climate information for quantitative decision making under uncertainty.  Throughout the course, students will have the opportunity to develop hands-on experience of working with climate datasets and interpreting their findings, as well as applying methods to deal with climate uncertainty through weekly lab sessions. Students further develop their real world problem solving skills by designing a group project on decision making for a chosen climate-sensitive system, such as agricultural planning, public health, energy and water management, to explore how to integrate climate science and its societal impacts for real world applications.

Skills Developed:

  • Statistical methods
  • Climate data analysis
  • Decision making under uncertainty
  • Matlab/Excel
  • Group project and presentations