651-3660-00L  Analysis of Time Series in Environmental Physics and Geophysics

SemesterSpring Semester 2021
LecturersF. Haslinger, A. Obermann
Periodicityyearly recurring course
Language of instructionGerman


AbstractIn geoscience we are often collecting vast digitally recorded. Such time-series data can be processed to emphasize particular aspects of the signal, an enormous advantage over paper records.
We introduce fundamental tools and concepts of time-series analysis, e.g. deterministic vs stochastic processes, signal correlation, and Fourier analysis.
ObjectiveUnderstanding of various methods for the analysis of time-dependent data.
ContentBased on various data sets we illustrate basic principles of time series and apply different methods of analysis:
deterministic and stochastic processes, stationary and non-stationary processes, sampling theorem, trend analysis, auto- and cross-correlation,
frequency analysis (Fourier Transformation).

The exercises require basic knowledge of MATLAB.
Lecture notesLecture notes and exercises are made available.
Literature- R. H. Shumway and D. S. Stoffer: Time Series Analysis and its Applications. Springer, New York, 2000.
- W.H. Press, B.P. Flannery, S.A. Teukolsky und W.T. Wetterling: Numerical Recipes: The Art of Scientific Computing. Cambridge University Press.
Prerequisites / NoticePrerequisites: equivalent to the first three semester of an earth science or environmental science curriculum.

Basic knowledge of matlab