Time series, a sequence of observations given at a sequence of time points, are ubiquitous in geosciences. Two main branches of time series analysis exist. Methodologies applied in the time domain and frequency domain analysis tools (‘spectral analysis’).  In this course you will learn the basic concepts of time series analysis using both complementary approaches. A special focus is on the application of these methods to geological or climate related datasets also discussing pitfalls and caveats.

Schedule
4 days, every morning theory, afternoon computer practise + one theory slot inbetween

Day 1: Characteristics of Time Series & Exploratory Data Analysis
Afternoon: Introduction into time-series analysis with R

Day 2: Time-series models, regression, linear filters
Afternoon:  time-series analysis on own or supplied datasets

Day 3: Fourier transform & power spectrum 
Afternoon: Numerical experiments spectral vs. time domain

Day 4: Spectral estimation, strategies and pitfalls
Afternoon: spectral analysis on own or supplied datasets

At the end of this course you are able to understand and apply linear time-series modelling, spectral analysis and the exploratory analysis of time-series using tools in the time and frequency domain. You will be able to perform these analyses using the statistical software R and to better judge published results involving time-series analysis.

tba

Shumway, R. H., & Stoffer, D. S. (2017). Time Series Analysis and Its Applications: With R Examples (4th ed.). Springer International Publishing. https://doi.org/10.1007/978-3-319-52452-8