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This Online Course in Climate Time Series Analysis is tailored for
postdocs and advanced PhD students working at the interface of
climate science and time series analysis.
No prior formal training in statistics is required;
familiarity with basic mathematics is assumed.
The course also appeals to established researchers
wishing to update their knowledge or acquire
new statistical techniques. Participants typically
come from climatology, ecology, econometrics,
environmental sciences, geosciences, hydrology,
meteorology, chemistry or physics,
as well as related sustainability fields.
ACRE Scholarship: Limited, need-based fee reductions are available for early-career researchers/students. See "Registration" below for how to apply.Accessible and well-supported: intensive online delivery with live-chat support and guided exercises. Key concepts are revisited across modules to consolidate understanding. What makes it different from other online courses? First, you have streaming access to carefully designed, recorded and edited lecture videos throughout the course and until the end of the two-month feedback period. You can pause and rewatch as needed, and you retain the slide deck for study. Second, daily live-chat sessions via a video platform during the course enable you to prepare questions and obtain comprehensive answers. Third, original analysis software — built to extract the most from noisy climate time series and documented in peer-reviewed publications — expands your analytical toolkit. Fourth, a two-month feedback period after the course (via email and, where appropriate, an online meeting) preserves the interactive mode of shared data analysis, allowing you to pursue real applications, including on your own data. Don't worry if formulas make you hesitate — you will learn both the basics and advanced methods here. You'll gain the required statistical tools and extensive hands-on training to analyse your data optimally and answer climate-related questions. You'll acquire the theoretical foundations needed to understand the tools and interpret results, and you'll learn to quantify uncertainties from data, climate models and statistical estimation. Climate case studies illustrate how the tools help you get the most from your data — and how to publish results in a thesis or research paper. Examples include:
The course instructor, Dr. Manfred Mudelsee — trained in physics, geology and statistics — has long-standing expertise in teaching statistical methods to non-specialists. What you getLectures and hands-on tutorials. Carefully structured lecture videos with guided exercises. Early access (before the course). As soon as materials go online (10+ days in advance) you receive streaming access to the lecture videos, the full slide deck (PDF), datasets, software and selected readings (PDFs). Included: an e-book version of the textbook (Mudelsee, 2014, Climate Time Series Analysis, 2nd edition, Springer, 454 pp). During the course days. Daily live-chat sessions (typically up to one hour) for questions and comprehensive answers; streaming access continues. After the course. A two-month individual feedback period (email and, if helpful, one-to-one online meetings). Streaming access remains available until the end of this period. Bring your own data. Strongly encouraged. The course is limited to 10 participants to allow in-depth individual consultation. Free preview. Module 01 "Introduction (Lecture)" is freely available on YouTube. Past participants: country listArgentina, Australia, Austria, Bangladesh, Belgium, Brazil, Canada, Chile, China, Colombia, Croatia, Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, India, Indonesia, Ireland, Italy, Japan, Latvia, Luxembourg, Nepal, Netherlands, Nigeria, Norway, Poland, Portugal, Saudi Arabia, South Africa, South Korea, Spain, Sweden, Switzerland, Ukraine, United Kingdom, United States of America, UruguayPast participants: referencesKarolina LeszczynskaGeohazards Research Unit, Institute of Geology, Adam Mickiewicz University, Poznań, Poland In January 2025, I participated in the Climate Time Series Analysis course. It was a unique opportunity to explore statistical methods used for analysing paleoclimate data. One of the advantages of this course is that you can participate remotely and still be in constant contact with the lecturer, Manfred Mudelsee. Complex topics are presented not only in an accessible way but also in a highly aesthetic format. Everything is refined down to the smallest detail. Regular meetings with the instructor allow for immediate clarification of doubts and questions. Another invaluable aspect is the ability to revisit the content whenever a deeper review is needed. The weekly structure of the course encourages commitment – if you're going to do this course, it's worth setting aside the time to concentrate on it. István Gábor Hatvani Research Centre for Astronomy and Earth Sciences, Eötvös Loránd Research Network and Center of Environmental Studies, Eötvös Loránd University, Hungary As a researcher at the beginning of his career, it was extraordinary to see such an established scholar speaking the language of the young. The short course I attended was practice-oriented, and all of his explanations were 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 have had. Henrieka Detlef School of Earth and Ocean Sciences, Cardiff University, UK 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. Registration
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