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This Online Course in Climate Time Series Analysis is specifically tailored to the needs of PhD students and postdocs, who want to learn about an important combination of disciplines (climate change and time series analysis), but who have not had much exposure to in-depth statistical teaching. It will also attract professional researchers who wish to update their knowledge or learn new statistical techniques. We expect participants to come from a background in climatology, ecology, econometrics, environmental sciences, geosciences, hydrology, meteorology, chemistry, physics or other sustainability sciences. We aim to be accessible to students at the beginning of their careers. We achieve this through an intensive online, chat-supported format combined with a repetitive, caring approach. What makes it different from other online courses? First, the course provides videos that have been carefully designed, recorded and edited. You can watch the videos over and over again, pausing as necessary. You receive the course slides and can study them again. Second, daily chat sessions on a video platform throughout the course allow you to prepare questions in advance and get comprehensive answers. Third, proprietary software designed specifically to get the most out of "dirty" climate time series data will add to your arsenal of analytical tools. Fourth, the individual feedback period of one month after the course (via email and possibly an online meeting) preserves the interactive mode of shared data analysis, allowing you to go deeper into 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:
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 ten days before the start to allow to optimally prepare yourself. During the course days, you can participate daily in online chats on the material delivered on that day. After the course, you are offered an individual one-month feedback period where you have the chance to show (more) own data, tell me about your questions, 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 listAustralia, 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, Ukraine, United Kingdom, United States of America, UruguayPast participants: referencesThis 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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! 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. 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. Registration
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