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46th Online Basic Course in Climate Time Series Analysis

3 to 7 July 2023

This Online Basic Course in Climate Time Series Analysis is specifically tailored to the needs of PhD students and postdocs, who wish to learn about an important combination of disciplines (climate change and time series analysis), but have had so far not much exposure to in-depth statistical teaching. It will also attract professional researchers, who wish to update their knowledge or to learn new statistical techniques. We assume that participants come from somewhere in the range of climatology, ecology, econometrics, environmental sciences, geosciences, hydrology, meteorology, or physics.

The basic format means that this course focuses on basic univariate concepts, such as trends and extremes, and that we aim for easy accessibility also for those students who are early in their career. The online version emerged in response partly to the Covid-19 situation (which started in 2020), but also to the general upward trend in need of electronic high-level quality education.

What distinguishes this from other online courses? First, the course provides videos that have been designed, recorded and edited with care. You can go repeatedly through the videos and make breaks as you need. You receive and can study again the delivered course slides. Second, daily chat meetings via a video platform over the full course duration allow you to prepare questions beforehand and get extensive response. Third, own-developed software, specifically designed to get the most out of "dirty" climate time series data, will enhance your arsenal of analytical tools. Fourth, the individual feedback period of two months post-course (via email and, possibly, online meetings) preserves the interactive mode of joint data analysis, it allows to go in depth through real applications — perhaps on your own data!

We just assume that do not run away when you see a mathematical formula: all the basics, and the advanced methods as well, you will learn here. You get the required statistical tools and extensive hands-on training to become able to optimally analyse your data and answer the associated questions about the climate. You acquire the theoretical basis for understanding the tools and interpreting the results. You learn to quantify the various sources of uncertainty in data, climate models and statistical estimation.

Climate case studies serve to illustrate the usefulness of the tools: how to make the most of your data by means of statistics — and how to publish it in a thesis or a research paper. Examples include:

  • Trend estimation techniques for the quantification of global warming (Mudelsee 2019 Earth Science Reviews 190:310)
  • Modelled river runoff and river floods during the past decades and centuries (Mudelsee et al. 2003 Nature 425:166, St. George and Mudelsee 2019 Journal of Flood Risk Management)
  • Paleohurricane risk during the past millennium from proxy series (Besonen et al. 2008 Geophysical Research Letters 35:L14705)

The course instructor, Dr. Manfred Mudelsee, trained in physics, geology and statistics, has a long-standing expertise in teaching statistical methods to non-specialists.

What you get. The course consists of lectures and extensive hands-on training in computer tutorials. Access to the course videos is provided through a streaming host. Data, software, the lecture as PDF, additional reading material (articles as PDF), the statistical tools and (optionally) an e-book version of the textbook (Mudelsee, 2014, Climate Time Series Analysis, 2nd edition, Springer, 454 pp) are included in the fee. You receive the link to the course slides already several days before the start to optimally prepare yourself. During the course days, you can participate daily in an online chat on the material delivered on that day. After the course, you are offered an individual two-month feedback period where you have the chance to shown (more) own data, tell me about the questions (the data are asking), receive support on the software and general statistical advice. We communicate by email during this period and, if needed, via one-to-one online meetings.

Participants are strongly encouraged to bring their own data for discussion and analysis during the course. The number of participants is limited to twenty to allow in-depth individual consultation with the course holder and textbook author, Manfred Mudelsee.

You want to have a free look? Please try Module 01 Introduction (Lecture), which is in the public domain.

Past participants: country list

Australia, Austria, Bangladesh, Belgium, Brazil, Canada, Chile, China, Croatia, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, India, Indonesia, Ireland, Italy, Latvia, Luxembourg, Nepal, Netherlands, Nigeria, Norway, Poland, Portugal, Saudi Arabia, South Africa, South Korea, Spain, Sweden, Switzerland, United Kingdom, United States of America, Ukraine, Uruguay

Past participants: references

This exciting online course provides deep insight into theoretical concepts which were familiar but never really understood. Overall, the course is well constructed and the material of high quality. I could largely follow the explanation but the density of the given material will require revising more than once the different concepts before allowing a full application to my own data. Therefore, the video format is of clear advantage as it allows coming back at your ease to the theoretical part. The chats provide also good opportunities to discuss the theoretical concepts and results from the exercises.
Marc Luetscher
Swiss Institute of Speleology and Karstology
La Chaux-de-Fonds, Switzerland

This online course was just the one I had expectations for. All of the statistical theory for climate change I had known before by self-learning was just separate tools, which I did not know how to put in order to work properly for the estimation of time series. Due to the well-organized structure of the course, I could understand properly separate elements and then make a holistic understanding of the climate process by statistical means. I think the course fits well both newcomers and experienced researchers in the field. The first ones can get the strategy for successful research and the others can dive deeper into the advanced tools as well as discuss innovations in the field.
Dariia Kholiavchuk
Yuriy Fedkovych Chernivtsi National University, Ukraine

As a researcher at the beginning of his career, it was extraordinary to see such an established scholar speaking the language of the young. His short course I attended was practice oriented, and all of his explanations straightforward. Since the students were not only allowed but encouraged to bring their own problems/data, this was truly a lesson for all of us. We could not ask a question he could not have answered in a more professional and comprehensive manner. All-in-all, it was one of the most useful courses in time series analysis I had.
István Gábor Hatvani
Research Centre for Astronomy and Earth Sciences, Eötvös Loránd Research Network and Center of Environmental Studies, Eötvös Loránd University, Hungary

Learning from Dr. Mudelsee, an expert in his field, was of tremendous help in gaining expertise in quantitative time series analysis. The lectures provide an excellent overview on fundamental concepts of time series analysis and together with the tutorial exercises I acquired the theoretical basis for understanding and interpreting the results for my first publication. The provided software was not only useful for my project but became popular within my section. Further I was charmed by the nice venue, the wonderful food and the picturesque village of Heckenbeck.
Theresa Grunwald
Deutsches Geoforschungszentrum GFZ
Potsdam, Germany

I very much enjoyed the course, both the content and the format. It is a very intense course, with a lot of relevant information. I found the tutorials very helpful. I want to thank you for being such a good host, for taking the time to patiently explain even basic stuff, for providing a friendly and open atmosphere and, of course, for all the delicious food, snacks and drinks.
Alexandra Engstrom-Johansson
Max Planck Institute for Chemistry
Mainz, Germany

The course is very helpful and gives great insight into statistical methods important in paleoclimate research. I've already used some of the software to analyse my data and it has proven to be extremely useful.
Henrieka Detlef
School of Earth and Ocean Sciences
Cardiff University, UK

Manfred's course armed us with the theory and tools behind some of the most fundamental and useful climate data analysis techniques. It is also a respite from the fast-paced lifestyle of wherever one is coming from; Heckenbeck is picturesque throughout the seasons, making for a relaxing environment to learn the tools of the trade.
Christopher S. Kelly
Department of Earth, Environmental and Planetary Science
Brown University, USA

The course of Climate Time Series Analysis is of high potential for climate studies and since I am dealing with meteorological data, I think that Dr. Mudelsee's methods and tools are highly beneficial to analyse trends, climate extremes, correlation and sensitivity. As an MSc student, I was a bit afraid to attend this course but Dr. Mudelsee has very patiently and calmly explained all tools in detail, the methodologies and the formulations behind everything. This has made the course even more exciting and understandable.
Monica Sharma (India)
Masters Environmental Geoscience
TU Bergakademie Freiberg, Germany

I attended Dr. Mudelsee's Advanced Time Series Analysis course in January 2017 as a PhD student. The restricted number of participants allowed Dr. Mudelsee to tailor the course based on the individual needs of each participant, as well as creating an open atmosphere for discussion. Some of the methods taught in the course can be hard to learn out about elsewhere, unless you know precisely what you are looking for. Furthermore, the course deals with statistical pitfalls commonly encountered in the climate sciences, that you will want to know about before you submit your work for publication. I strongly recommend the Advanced Time Series Analysis course at CRA.
Karl Nyman
Centre for Ice and Climate, Niels Bohr Institute
University of Copenhagen, Denmark

As a paleoclimate researcher, I know that it is always necessary to connect my own sets of data with time. All of these datasets will only have meaningful interpretations when linked to records associated with time-dependent series and processes. I have this thinking when I started looking for a course that can help me with my data analysis. The climate time series course analysis offered by Manfred Mudelsee is just the perfect course to take for this purpose. I also like it that the last sessions were allotted for presenting our own data in class, get some feedbacks, and analysing them on the spot with our own software choice.
Deborah Tangunan
MARUM – Center for Marine Environmental Sciences
University of Bremen, Germany

For me the course was very useful. It has broadened my knowledge in the statistical methods that I used so far, and opened new avenues for my future research. Dr. Mudelsee nicely points to the important questions and to the ways of inference from statistical methods in practical problems. Additionally, it is worth to mention delicious organic homemade meals in Heckenbeck!
Ksenija Cindric Kalin
Meteorological and Hydrological Service
Zagreb, Croatia

I therefore think that attending such a course is of high interest to paleoclimate researchers, especially those who are looking for climate mechanisms, feedbacks and lead and lags of different climatic components. However, I would advise to have beforehand all the statistical and mathematical concepts readily 'charged' and fresh in your brain. Therefore one doesn't loose too much time trying to remember what's variance, how is the Pearson's coefficient calculated, what t-Student stands for or even what characterizes a Gaussian curve. Finally, it was a privilege to work and receive advice from Dr. Manfred Mudelsee, to focus on my and participate on other colleagues problem solving and always in a very comfortable, familiar and cozy environment.
Catarina Dinis Cavaleiro
MARUM – Center for Marine Environmental Sciences
University of Bremen, Germany

As the head of the Geomathematical and Informatics Section of the Hungarian Geological society, I invited Dr. Mudelsee to give a short course to colleagues from all fields of science (oil industry, mining, climate modellers, university lecturers in geomathematics, water researchers, etc.) prior to our biannual meeting. I can only say the very best of him, since all attendees who contacted me afterwards were thrilled and very much satisfied with what they received for their money. I am hoping to be able to collaborate with Dr. Mudelsee in the future.
Ferenc Fedor
Head of the Geomathematical and Informatics Section of the Hungarian Geological Society, Hungary


  • Twenty participants maximum: first come, first serve
  • Deadline for registration: 23 June 2023
  • Information requested: name, email, academic title(s), affiliation(s) and professional status(es), research field(s) and computer operating system(s) please also indicate whether you wish own data to be analysed during the course or during the post-course feedback period; finally, please attach a short CV including list of recent papers, abstracts and links since this helps to better prepare for your needs — please put all this into the registration form (PDF)
  • Send the information (i.e., the completed registration form) by email to the course email address
  • After receiving your registration email, an official payment request is sent to you electronically, which you kindly let your institution pay; this payment completes the registration. It is possible to pay via credit card. Afterwards, the course invoice will be sent electronically to the paying institution. The aim is to have the payment done before course start.

Included in registration fee

  • Course lecture and tutorial as module videos (about 10 hours in total, streamed, protected online access):

    • Day 1 (Monday, 3 July 2023): Module 01 Introduction (Lecture)
    • Day 1 (3 July): Module 02 Introduction (Tutorial)
    • Day 2 (4 July): Module 03 Persistence Models (Lecture)
    • Day 2 (4 July): Module 04 Persistence Models (Tutorial)
    • Day 3 (5 July): Module 05 Bootstrap Confidence Intervals (Lecture)
    • Day 4 (6 July): Module 06 Regression I (Lecture)
    • Day 4 (6 July): Module 07 Regression I (Tutorial)
    • Day 5 (7 July): Module 10 Extreme Value Time Series (Lecture)
    • Day 5 (7 July): Module 11 Extreme Value Time Series (Tutorial)
    • Day 5 (7 July): Open Session: Re-cap, Open Questions, Joint Data Analyses, Individual Presentations, Outlook

  • Daily chat during course days on modules from that day
  • Course slides (252 pages, PDF, downloadable, protected online access)
  • Data, software (Windows executables and selected Fortran source codes) and reading material (downloadable, protected online access)
  • Caliza™ 3.0 software, full version is included in software
  • Two months individual post-course feedback period, software support and general statistical advice
  • Optional: Textbook Mudelsee 2014 Climate Time Series Analysis, 2nd edition, Springer, 454 pp. (e-book version)

Registration fee (net price, excluding 19% VAT)

  • Without e-book: 800 EUR
  • With e-book: 900 EUR


  • Climate Risk Analysis, Kreuzstrasse 27, Heckenbeck, 37581 Bad Gandersheim, Germany (CRA)
  • Contact person: Dr. Manfred Mudelsee, phone +49 5563 9998140


  • Language: English (during the individual post-course feedback period, German is also possible)
  • Computer: essential for doing the tutorial, please note that you should have administrator rights to be able to install software
  • Laptop operating system: Windows preferable but not mandatory, Linux also works
  • Mac users: prior to the start of the course, install a Windows emulator (see, e.g., Oracle VM,; Wine,; or Homebrew,; if uncertain, please do consult someone from the computing department of your institution
  • Computing environment: the course accomodates virtually all you bring (Matlab, Python, R, S-Plus, etc.)
  • Data: you are very welcome to bring your own data for analysis! Data format: ASCII (more details in our confirmation email)
  • Reading material: a few topical papers are provided


  • Detailed list of taught topics
  • Electronically signed and sent by email to you
  • Provided at the end of the course


  • For distribution at your institution (thank you!)
  • high-resolution DIN A4 PDF
  • Flyer


  • Electronically signed and sent by email after payment


#1 Deadline for registration Fri 23 June 2023
#2 Confirmation email: details on received registration and payment; course chat hours and timezone latest Fri 23 June 2023
#3 Welcome email: access to the full course material (links, passwords), advice for home preparation Mon 26 June 2023
#4 Start of course Mon 3 July 2023
#5 End of course Fri 7 July 2023
#6 Course certificate email Fri 7 July 2023
#7 End of two-months individual post-course feedback period Thur 7 Sep 2023

A very warm welcome!