This course will offer an advanced introduction to climate data analysis. It is intended for graduate students studying climate science and is mainly laboratory (computer) based. For the first part of the course, the goal is to provide an understanding of the theory underlying the statistical analysis of climate data, in the space, time and spectral domain. In the second part of the course, the basic concepts of time series analysis will be introduced in terms of identifying stationarity or trends in the data. Some of the important statistical estimation techniques such as regression, correlation and spectral analysis will be used for the time series analysis by giving a detailed account on the interpretation of the data and the associated climatological questions. Although some previous knowledge of probability and statistics will be helpful, a review will be provided at the beginning of the course. Concepts and notation will be reintroduced, as needed. If time permits, the statistical modelling approach will also be covered.
Note: This is a mandatory course for the students in the Climate Change Impacts and Adaptation field of study. *
this course is not being offered in the 2022-23 academic year. Students in the CCIA program must enroll in EES1119 to meet their program requirements.
Most current timetable information
Most recent syllabus available for download