Statistical methods for climate science
The course covers the basic tools from statistics and machine learning that are used to analyze weather and climate data, in time series or gridded fields.
Climate may be defined as “the statistics of weather". In this course you will learn the basic concepts of statistics and machine learning, and apply them to atmospheric and oceanographic data. The course covers the statistical analysis of time series, and the analysis of spatially distributed fields by using empirical orthogonal functions (EOFs). It also covers artificial neural networks and the algorithms of supervised and unsupervised learning.
Information for admitted students autumn 2024
Congratulations! You have been admitted at Stockholm University and we hope that you will enjoy your studies with us.
In order to ensure that your studies begin as smoothly as possible we have compiled a short checklist for the beginning of the semester.
Follow the instructions on whether you have to reply to your offer or not.
universityadmissions.se
Checklist for admitted students
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Activate your university account
The first step in being able to register and gain access to all the university's IT services.
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Register at your department
Registration can be done in different ways. Read the instructions from your department below.
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Read all the information on this page
Here you will find what you need to know before your course or programme starts.
IMPORTANT
Your seat may be withdrawn if you do not register according to the instructions provided by your department.
Information from the department - courses
Welcome to your studies at the Department of Meteorology, Stockholm University.
All accepted students receive a welcome letter via email with important information for their studies.
Roll Call
At MISU, the course starts with a mandatory roll call. You will get more detailed information about the roll call via email. If you plan to start the education but for some reason cannot participate at the roll call, please contact our study counselor. Otherwise you risk losing your spot in the course. Contact information for the study counselor is listed at the bottom of this page.
Registration
If you are accepted to a course, you can register for it through your University account.
You can register online in Ladok, by logging in with the "eduID" or "Universityadmissions.se" options. Please note that you cannot log in with the option "Access through your institution".
If you have problems registering, please contact our study counselor. Contact information is listed at the bottom of this page.
Conditionally accepted
If you have been accepted with conditions then you must contact the study counselor before you can start the education. Please do this as soon as possible and well ahead of the start of the course. Contact information is listed at the bottom of this page.
On a waiting list
Have you received information that you are on a waiting list for a course? You will always be contacted by us via email if you are accepted. Generally, we do not accept anyone from the waiting list beyond 1 week into the semester.
Find your way to MISU
MISU has its own lecture rooms and all of them are in the same corridor as the rest of the department. You will get your own entry card for access to the department. MISU is located on 6th floor, building C in the Arrhenius Laboratories.
Classes during the coming semester
You can find more detailed information about each individual course via the teaching platform Athena. You will get access to each respective course page as soon as you activate your University account and have been registered for the course. If you have any questions, please contact the study counselor (contact information below).
Contact
Study counselor
Phone: 08-162418
Email: studievagledare@misu.su.se
Welcome activities
Stockholm University organises a series of welcome activities that stretch over a few weeks at the beginning of each semester. The programme is voluntary (attendance is optional) and includes Arrival Service at the airport and an Orientation Day, see more details about these events below.
Your department may also organise activities for welcoming international students. More information will be provided by your specific department.
Find your way on campus
Stockholm University's main campus is in the Frescati area, north of the city centre. While most of our departments and offices are located here, there are also campus areas in other parts of the city.
Read more
For new international students
Climate may be defined as “the statistics of weather". In this course you will learn the basic concepts of statistics and machine learning, and apply them to atmospheric and oceanographic data. The course covers the statistical analysis of time series, and the analysis of spatially distributed fields by using empirical orthogonal functions (EOFs). It also covers artificial neural networks and the algorithms of supervised and unsupervised learning.
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Course structure
The course covers the following topics:
- Basic concepts of probability and statistics
- Time series analysis
- Statistical significance and hypothesis testing
- Spectral analysis
- Linear regression
- Empirical orthogonal functions and extensions
- Analysis of variance – ANOVA
- Supervised learning (classification)
- Unsupervised learning (clustering algorithms)
- Artificial neural networks
- Applications to weather forecasting
Teaching format
Lectures and computer lab
Course materials
Grading criteria, course literature and other material and correspondence related to the course will be available on the course Athena site at https://athena.itslearning.com once you have registered for the course.
Assessment
Assignment in the form of a written project
Examiner
Here is a link to a list of course coordinators and examiners.
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Schedule
The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course.You can search for schedules from previous years in TimeEdit, by entering the course code.
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Course literature
Note that the course literature can be changed up to two months before the start of the course.
- Hannachi, A., 2022: Statistical Climatology. Compendium. (Provided by MISU).
- Hannachi A., 2021: Patterns Identification and Data Mining in Weather and Climate, Springer-Verlag, 600pp. ISBN 978-3-030-67072-6. (Provided by MISU)
- von Storch, H., and F. W. Zwiers, 1999: Statistical Analysis in Climate Research. Cambridge University Press, Cambridge. (Provided by MISU)
- Shah C. 2022: A Hands-On Introduction to Machine Learning. Cambridge University Press, Cambridge. ISBN: 9781009123303.
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Course reports
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Contact
Study counselor
