25th Training Course for Beginners in
Climate Time Series Analysis

25 February to 1 March 2019

This Training Course for Beginners in Climate Time Series Analysis is specifically tailored to the needs of MSc students, PhD students and postdocs, who wish to learn about an important subject (time series analysis), but have had so far not much exposure to in-depth mathematical or statistical teaching. It will also be attractive for professional researchers, who wish to update their knowledge. We assume that participants are from somewhere in the range of climatology, ecology, environmental sciences, geosciences, meteorology or hydrology.

A significant part of the course part is devoted to training in "Open Sessions", where we recapitulate concepts, answer basic and advanced questions, discuss applications and devote time to in-depth analyses of 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:

  • Dynamics of the Pliocene Northern Hemisphere Glaciation (Mudelsee and Raymo 2005 Paleoceanography 20:PA4022) and the Cenozoic climate evolution (Mudelsee et al. 2014 Reviews of Geophysics 52:333)
  • Paleohurricane risk during the past millennium from proxy series (Besonen et al. 2008 Geophysical Research Letters 35:L14705)
  • Modelled river runoff and river floods during the past decades and centuries (Mudelsee et al. 2003 Nature 425:166, St. George and Mudelsee 2018 Journal of Flood Risk Management)

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. Data, software, the lecture as PDF, the statistical tools and a printed copy of the textbook (Mudelsee, 2014, Climate Time Series Analysis, 2nd edition, Springer, 454 pp) are included in the fee. You get the link to the course PDF already one week before the start to optimally prepare yourself. After the course, you are offered a one-month period where you may receive support on the software and general statistical advice.

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

An ice-breaker meal, a course dinner and daily organic lunch (vegetarian or vegan if requested), snacks, coffee and tea are included. A shuttle service to/from the railway station and your accomodation in Bad Gandersheim are also covered by the registration fee.

Participants of past courses have praised the intellectual, co-operative atmosphere during the courses, the family-like setting and the nice rural landscape around here: please see their comments below. Heckenbeck is a little village of high ecological awareness, which belongs to the medieval town of Bad Gandersheim.

The new lecture house, without barriers, has opened in summer 2015.

Past participants: country list

Australia, Austria, Belgium, Brazil, Canada, Chile, Croatia, Czech Republic, Denmark, Finland, France, Germany, Indonesia, Ireland, Italy, Nepal, Netherlands, Nigeria, Norway, Poland, Portugal, South Korea, Spain, Switzerland, UK, USA

Past participants: references

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


  • Email to
  • Deadline for registration: 15 February 2019
  • Eight participants maximum: first come, first serve
  • Give your name, research field, affiliation with address and country, laptop operating system, mobile phone, dietary preferences, special needs; preferably: information about your booked accomodation; optional: second email address, fax
  • Please attach also (single PDF) your CV and the abstract of a recent paper or thesis you are working on, since this allows us to better prepare for your needs
  • Give name of paying institution together with its address and, if applicable, VAT ID number; note that institutions within the EU (but ouside of Germany) may qualify for the reverse-charge mechanism, please check beforehand with your paying institution
  • Your first email address appears on messages sent to all participants, other details may be kept confidential upon your request (please inform us in the registration email)
  • Contact us if in need of more information (visa, invitation letter, VAT, etc.)
  • 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.

Included in registration fee

  • Textbook: Mudelsee 2014 Climate Time Series Analysis, 2nd edition, Springer, 454 pp. (softcopy)
  • Lecture (PDF; USB stick)
  • Data and software (Windows executables and selected Fortran source codes; USB stick)
  • Caliza™ 3.0 software, full version (official net single price, 900 EUR)
  • One month post-course software support and general statistical advice
  • Organic meals: ice-breaker (Sunday evening), lunch (Monday to Friday), course dinner (Thursday evening)
  • Organic snacks, coffee and tea (Monday to Friday)
  • Daily shuttle service (to/from railway station Kreiensen, to/from accomodation option Bad Gandersheim)

Registration fee (net price, excluding 19% VAT)

  • Regular registration: 1280 EUR


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


  • Language: English
  • Audience: MSc students, PhD students, postdocs and professional researchers in climatology, ecology, environmental sciences, geosciences, meteorology or hydrology
  • Laptop: essential for doing the tutorial, bring your own; 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., Wine,; Homebrew,; or Xcode,; if uncertain, please do consult someone from the computing department of your institution
  • Internet connection: via LAN cables, which are provided by CRA (please check your laptop's connections)
  • 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! During the course, you have the chance of giving a mini presentation of your data and work! Data format: ASCII (more details in our confirmation email)
  • Evening reads: a few recent topical papers are provided


  • Detailed list of taught topics
  • ECTS or other credit points: the work load estimate is 30 hours during the course week plus 30 hours for preparation on basis of the lecture PDF (which is made available at least one week before the start of the course); students may use the certificate (over 60 hours work load) to claim credit points from their educational institution
  • Provided on the last course day

Time schedule (exact hours to be fixed on course Monday: your suggestions welcome)

  Arrival Sun 24 February 2019
  Ice-breaker at CRA Sun 19.30
  Preliminary (Badge, Book, Invoice, USB Stick) Mon 25 Feb 2019
    Lecture Tutorial
1.     Introduction Mon 10–11 Mon 11–13
2. Persistence Models Mon 14.30–15.30 Mon 15.30–17.30
3. Basic Mathematics (Expectation, Variance, etc.) Tue 10–11  
4. Bootstrap Confidence Intervals Tue 11–13
5. Regression I Tue 14.30–15.30 Tue 15.30–17.30
6. Spectral Analysis Wed 10–11 Wed 11–13
7. Extreme Value Time Series Wed 14.30–15.30 Wed 15.30–17.30
8. Correlation Thur 10–11 Thur 11–13
9. Open Session I (Re-Cap, More Applications, More Theory, In-Depth Analyses, Individual Consultations, etc.) Thur 14.30–17.30
10. Course Dinner at CRA Thur 19
11. Open Session II
Course Certificate
  Fri 10–13
    Farewell (Lunch or Lunch Package) Fri 1 March 2019


  • Climate Risk Analysis, Course/Office Building, Kreuzstrasse 27, Heckenbeck, 37581 Bad Gandersheim, Germany
  • Contact phone: +49 5563 999246 and +49 5563 9998140
  • New, modern bungalow
  • Barrier-free
  • Picturesque medieval town Bad Gandersheim; nice rural landscape with high ecological awareness in and around Heckenbeck (which is approximately 5 km to the west of the centre of Bad Gandersheim); intellectually stimulating, co-operative atmosphere and family-like setting at CRA and in the village
  • External Link: Heckenbeck on TV [in German]
  • Local organic food store in walking distance: Grüne Tomaten
  • Option to take meditation or Ashtanga/Kundalini yoga lessons in Heckenbeck (please indicate wish in the registration email)
  • Option to take bodywork or osteopathy treatment in Heckenbeck (please indicate wish in the registration email)


A wide range of room types (see below) is available but their number is limited. It is therefore advisable to book early. Please contact CRA if you need additional information or help with the booking.
  • CRA's Guest Studio: at the venue, one place (single) maximum, breakfast and supper included, E-bike rental included, sauna, LAN, 80 EUR per night and person, high quality (***)
  • Gerichtsschänke Bad Gandersheim: about 5 min by taxi or 20 min by bike, single, double or triple rooms, breakfast included, WLAN, in the centre of Bad Gandersheim, approximately 50 EUR per night and person, good quality (**)
  • Pension "Bei Heidi" Bad Gandersheim about 3 min by taxi or 20 min by bike, WLAN, approximately 40 EUR per night, good quality (**)
  • Klosterhof Brunshausen: about 10 min by taxi or 40 min by bike, five places (single/double) maximum, breakfast included, WLAN, charming historical place in the the eastern part of Bad Gandersheim, approximately 40 EUR per night and person, good quality (**)
  • Rike's Guesthouse Heckenbeck: walking distance, one place (single/double) maximum, no breakfast but has kitchen, approximately 32 EUR per night and person, good quality (**), contact: Rike and Jürgen Rech, email
  • Anja's Charming Flat: walking distance, two rooms plus bath and kitchen, breakfast provided for Monday, approximately 35 EUR per night, good quality (**), contact: Anja Mertens, email
  • Room Mirabella Heckenbeck: walking distance, one place (single/double, charming eco place, no breakfast but has shared kitchen, via Airbnb, 20 EUR per night (plus 10 EUR for second person), good quality (**)
  • Weltbühne Heckenbeck: walking distance, six places (single/double) maximum, no breakfast but has shared kitchen, approximately 27 EUR per night and person, basic quality (*)


  • Hannover airport: HAJ, take S-Bahn to Hannover central railway station
  • Hannover central railway station: take local train to Kreiensen (~45 min)
  • Göttingen central railway station: take local train to Kreiensen (~20 min)
  • External Link: Deutsche Bahn railway
  • From Kreiensen to CRA: If you arrive not too late: call CRA at +49 5563999246 or +49 5563 9998140 to get picked up! If you arrive late: Taxi Kreiensen, better to call in advance, phone +49 5563 7777 (~10 EUR)
  • From Kreiensen to Bad Gandersheim: take local train or call CRA to get picked up. If you arrive late: Taxi Kreiensen or Taxi Bad Gandersheim
  • Taxi Bad Gandersheim: City Car, phone +49 5382 907908


#1 Deadline for registration Fri 15 Feb 2019
#2 Confirmation email: details of registration and payment, password for lecture-PDF, information about data format, welcome Sat 16 Feb 2019
#3 Lecture (PDF, password-protected) put online Sat 16 Feb 2019
#4 Arrival, accomodation, ice breaker Sun 24 Feb 2019
#5 Start of course Mon 25 Feb 2019
#6 End of course Fri 1 Mar 2019
#7 End of 1-month post-course support period on software and general statistical advice Mon 1 Apr 2019

A very warm welcome to Bad Gandersheim and Heckenbeck!