Fundamentals of Ocean/Atmosphere Data Analysis @ Oslo Research Park
May 11 – May 15 all-day

Responsible: Joe LaCasce / UiO
International lecturer: Jonathan Lilly / Theiss Research
Max. no. of participants: 12 CHESS students (total participants: 20)
Credit points: 2 ECTS
Registration form here. Deadline: 15 March
Submitted applicant list

Course description:  This course introduces students to essential statistical and conceptual tools for analyzing any type of dataset from oceanography, atmospheric science, or climate.

In this course, the students will learn how to use our creativity together with simple statistical tools to delve into datasets, uncovering whatever information they may contain, and how to shape that information into stories.  In particular, a powerful method called “distributional data analysis” allows us to deconstruct potentially large, multivariate datasets by examining their statistics in two-dimensional slices.  Careful attention is given to the variance ellipse, the fundamental second-order statistical quantity for bivariate data such as velocity.  Data organization and manipulation techniques, visualization strategies, and healthy coding habits are all also addressed.  Finally, the course provides innovative training in the essential mental factors of curiosity, imagination, and objectivity.

Students apply techniques to datasets of their own choosing using the Matlab programming language, and learn further through homework problems and group exercises.

This will be the fourth time a version of this course is offered in Oslo, and the second time focusing on a greatly expanded version of the “low-tech” methods that form the foundation of the data analyst’s toolbox.

This course is strongly recommended for all students wishing to participate in a more advanced time series analysis course with the same instructor, to be offered over two weeks in Fall 2020 at the Alfred Wegener Institute in Bremerhaven, Germany.

Learning modules/structure:  There will be two hours of lectures in the morning sessions and a two-to-three hour lab session in the afternoons. Lectures will be given in the mornings and lab sessions in the afternoons, allowing the students to apply the methods directly to data. The students will also complete a final project on data of their choice. The students employ the statistical and time series analysis toolbox jLab developed by the instructor (  Course notes are available online at (specifically chapters 1-8).

Learning outcomes: At the end of the course, students will be well-prepared to begin efficiently analyzing any dataset they might encounter, while avoiding common pitfalls.  Students gain practical experience through hands-on demonstrations and exercises in Matlab.

Prerequisites:  Students must have a fully functioning version of Matlab with jLab already installed at the start of the course.  Students are expected to bring a dataset of any type that they would like to analyze for a course project.  Multivariate datasets are encouraged.  Model output is also acceptable.

State of the Art Weather and Climate modeling @ Bjerknes Center, Bergen
Jun 2 – Jun 5 all-day

Responsible: Marvin Kähnert, Nadine Steiger, Sonja Wahl, Leilane Passos (UiB)
Credit points: 1 ETCS
Max no. of participants: 20
Registration deadline: 30 April, 2020
Registration form is here.
Participant submission list

**Due to the uncertainty of coronavirus development in the coming months, the workshop may move to online if needed.**

Course objectives:

Numerical models are crucial to scientific advancement. They compel scientific hypotheses to provide repeatable results, which can then be validated against measurements. However, few model training programs cover the spectra of existing models or prepare students for the practical use of models. Therefore, many PhD students are ‘stuck’ with a ‘learning-by-doing’ approach. What are the consequences of moving from the continuous to a discrete world and how is it handled? How does the interplay between hypotheses, models, and measurements look like in the form of schemes, data assimilation, and verification? How are model experiments designed?
This course aims to give insight into such question in a balanced mix between theoretical concepts and practical applications.


The course will start by introducing the basic concepts of numerical modelling and will then proceed to focus on specialized models such as climate, ocean and operational weather prediction models. Further, essential concepts like Data Assimilation, verification as well as innovative model diagnostics such as tracers or trajectory analysis will be covered. Students will get hands on experience with available tools for the efficient work with model data. Each lecture will be given by a respective expert from multiple institutions such as the University of Bergen, MET Norway, ETH Zürich or the Nansen Center. Poster/PICO sessions will further propel discussions between and among the participants and lecturers.


The participants are expected to have a keen interest in the concept and/or work with numerical models. Basic knowledge about working with Linux is appreciated. Upon registration the participants will be asked to give at least one pressing question of theirs regarding modelling. These questions will be integrated into the discussions and lectures.


* More efficient use of numerical models on a daily work basis
* Broader awareness of and knowledge about different types of models within geosciences
* Introduction to different ways of combining observations and models
* Networking among PhD students from different fields with modelling interest

Looking forward to welcoming you all in Bergen


Dallas Murphy’s annual Advanced Science-Writing Workshop – 2020 @ Geophysical Institute, University of Bergen
Jun 15 – Jun 19 all-day

Responsible: Dallas Murphy and Thomas Spengler
Credit points: 2 ETCS
Max no. of participants: 12
Registration deadline: 30 April, 2020
Registration form is here.
Participant submission list

**Due to the uncertainty of coronavirus development in the coming months, the workshop may move to online if needed.**


Only the science matters in science papers.  Often, however, good science is damaged by its unclear presentation in writing.  Clarity is the science writer’s sole stylistic obligation.  But without a cogent, carefully constructed literary structure, there can be no clarity; clarity is in structure.  We will, therefore offer techniques and means of attaining structure that can be applied to the present paper, the next paper, and the next.


– We can accommodate a maximum of 12 students.  Each will submit a draft of their papers 3 weeks before the workshop begins, and everyone will receive a package containing all papers.
– As a group, we will rigorously examine the abstracts, introductions, and conclusions for each paper, asking, first, are they clear?  We will address three papers per day, leaving Friday open for rewrites.
– Working together as a group, we will help improve the paper at hand.  But that alone is not enough.  We will use the papers as a starting point to establish the foundations of a practical writing process – of thinking like a writer about science writing – that will produce better papers, but also alleviate some of the stress most students feel about writing.
– Different faculty scientists will participate in each session to help students clarify the science itself.


Dallas Murphy is a professional writer, author of nine books, a mix of fiction and nonfiction, and two plays.  He conducts science-writing workshops at the Max Planck Institute for Meteorology, University of Hamburg, Max Planck Institute for Polymer Research, University of Miami, and Bergen Geophysical Institute.


ACDC summer school 2020 @ Abisko and Tarfala Research Stations, Abisko National Park, Sweden
Aug 16 – Aug 28 all-day

This year’s Advanced Climate Dynamics Course for PhDs will be in August in a spectacular location in northern Sweden.

Topic: Dynamics of the Global Water Cycle
Venue: Abisko and Tarfala Research Stations, Abisko National Park, Sweden
Dates: 16.– 28. August, 2020
Application deadline: 1. March 2020.
Target: advanced graduate students (PhDs). Other applications will be considered on a case by case basis if there is space (admission is competitive).
Goal: To mix diverse students and lecturers with empirical and dynamical training within climate science and focus on understanding the basic principles and dynamics relating the global water cycle.
Price: Expenses on site are covered by the school, participants must cover travel to the venue (Abisko train station:
Key topics to be included:
– Atmospheric moisture, clouds, and aerosols
– Extreme weather
– Ocean circulation and the freshwater budget
– Floods and flood variability
– Soil moisture and climate
– Water balance and agriculture
– Paleo evidence of the hydrological cycle
– Sea level and ice sheets
– Cryosphere, ice-ocean interaction, and ice-cores.

Check for details and continuous updates on list of lecturers and program.


For contact: