This course provides a foundation for analytical methods used in hydroclimate studies. The course is module-based, with a designated suite of methods. Each module has a specific focus on the types of problems and/or datasets, which lead to a selection of methods and approach, to solve a series of progressive questions related to the module topics. Topics include hydroclimatic extremes, climate change and variability, from diagnosis to modelling for predictions. The course will introduce the open source statistical computing and graphic language, R. Methods include time series analysis, regressions, pattern recognition & dimension reduction. Students are expected to complete an individual project using R. Some multivariate statistical analysis method (e.g. factor analysis, classification & clustering) and advanced modeling methods (e.g. Bayesian hierarchical modeling) might be introduced, if they are suitable for the students’ projects. Instructor's approval is needed.