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Ocean/Atmosphere Time Series Analysis: Theory and Practice

23.05.2016 - 27.05.2016

When: May 23-27. The lectures will run from 10-12 and from 13-14 every

Where: Oslo. Map for the Forskningspark. If you're coming by T-bane, go to the Forskningsparken stop and then walk down the little valley towards the building. The
first lecture will happen in "Hagen 1"

Who: Jonathan Lilly

Application deadline: May 1st

The purpose of this course is to introduce students to the most useful  tools and techniques for dealing with time series, with a focus on the particular needs of ocean/atmosphere research.  Actual use of these methods in practice, as well as their theoretical foundations, are both emphasized. Beginning with elementary statistics and Fourier basics, we will progress to the theory of stochastic processes, Fourier spectral estimation, and wavelet and time-varying spectral analysis. Students will have the opportunity to apply these techniques to datasets of their own choosing, as well as to solidify their understanding through homework problems and group exercises.


Students will gain a solid understanding of the foundations of spectral analysis, and become familiar with more advanced topics, including new techniques that have been developed by the lecturer and colleagues specifically for ocean/atmosphere applications. Particular attention will be paid to clarifying common misunderstandings and avoiding potential pitfalls. In addition, students will learn hands-on by working in Matlab, primarily using the statistical and time series analysis toolbox jLab, written by the lecturer and available online at  As time series methods are, for historical reasons, often not particularly emphasized within the oceanographic community, it is hoped that this course will help students gain a fluency with tools that could prove highly useful to them in their future research.


The course will be held over the week of May 23--27, with two hours of lectures in a morning session and a hour-long lab session in the afternoons. Problems and assignments will be given in order to help the students better understand the material.  Students are encouraged to bring a small time series dataset---for example, current meter records, drifter trajectories, or temperature time series---that they would like to analyze. In addition to the homework, supplemental reading material will be suggested to go along with each lecture.

Figure Jon Lilly course 

Figure: A rotary power spectral estimate of ocean surface current  velocities observed by NOAA's global drifter dataset, as a function of latitude. The black curve is the inertial frequency, while vertical dashed lines mark the tides.  This is formed using Thomson's tapering method, which will be covered in the course.

Participant list:

  1. Ylva Ericson, UNIS
  2. Ada Gjermundsen, UiO
  3. Kristoffer Aalstad, UiO
  4. Henrik Grythe, NILU
  5. Lisbeth Havik, UiB
  6. Siiri Wickström, UNIS
  7. Astrid Fremme, UiB
  8. Sunil Pariyar, UiB
  9. Lucas Becker, UiB
  10. lander Crespo, UiB
  11. Ingrid Onarheim, UiB
  12. Marius Årtun, UiB
  13. Marie Eide, UiB
  14. Bikas Bhattarai, UiO
  15. Carina Bringedal, UiB
  16. Kjersti Opstad Strand, HI
  17. Eli Anne Ersdal, UNIS
  18. Eli Børve, Akvaplan-Niva
  19. Hans Kristian Djuve, Akvaplan-Niva
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