Ocean/Atmosphere Time Series Analysis: Theory and Practice

Ocean/Atmosphere Time Series Analysis: Theory and Practice

Speaker: Jonathan Lilly, Planetary Science Institute
Organizers: MarDATA, sponsored by Helmholtz Information & Data Science Academy

Statistics — Fourier Spectra — Wavelet Analysis — Mental Factors

Course content: This course will introduce the doctoral researchers to classical as well as cutting-edge techniques for analysing time series in oceanographic, atmospheric science, and climate applications. Beginning with a solid understanding of the link between time domain and frequency-domain analyses, we will proceed from simple smoothing, to Fourier spectral estimation, to time-frequency methods such as the continuous wavelet transform. The chosen techniques are those that experience has shown to be the most useful in dealing with time series from the ocean and the atmosphere. Emphasis will be given to hands-on, practical application of methods, as well as to understanding the theory behind various methods. Extensive course notes may be found at http://jmlilly.net/course/index.html

Doctoral researchers can choose to participate in the course using either Python, Matlab, or for the first time, Julia. The participants will bring a dataset of their choice that they would like to investigate in detail. A final project will consist of applying the methods taught in the course to this dataset and interpreting the results. The doctoral researchers will receive personalized feedback, tailored to their specific datasets, through one-on-one meeting sessions with the instructor.

Learning modules/structure: The course will run Monday through Friday from June 05 to June 16 onsite at GEOMAR (Kiel). We will meet for five hours a day for ten days. Class time will be roughly split between lectures and interactive lab sessions. There will be a long half-hour break each day as well as several shorter breaks.

Target group: The course is open to doctoral researchers in marine and climate sciences or related data sciences
who are working with time series data sets. Place availability permitting, early postdoctoral researchers are equally invited.

Prerequisites: The participants should have a working knowledge of one of the programming languages the course is
offered in (Matlab, Python, or Julia). The course endeavours to be self-contained in that needed information will be covered during the course itself, however, prior experience with complexnumbers, e.g. u+iv, as well as linear algebra is expected. Those with questions should contact the instructor at jmlilly@psi.edu.

Registration: Total number of participants is limited to 35 (with 20 slots open for non-MarDATA members). Participation will be allocated on a first come - first serve basis. The registration is considered binding!

Please note that any costs for accommodation in and travel to Kiel are to be borne by the participants themselves!

Registration closes on May 22, 23:59
Please register by mail to info@mardata.de