Advanced Statistics Training for Climate Research 2019 @ Geophysical Institute, University of Bergen
Aug 19 – Aug 22 all-day

Lecturers: Prof David Stephenson and Dr Stefan Siegert from University of Exeter
Credit point: 1 ECTS
Max. no. of participants: 20
Registration form here.  Deadline 5 August
Submitted application list

Course description

This is a 4-day intensive course on statistical modelling concepts for climate scientists. Since it is impossible in such a short course to go into any great depth, this course aims instead to convey the fundamental modelling concepts in statistics and an understanding and ability of how to use them correctly to interpret climate data. The course will consist of eight lectures interspersed with multiple hands-on computer sessions.  

Learning Outcomes

  • Deeper appreciation of statistical modelling
  • Awareness of some relevant areas of advanced statistics
  • Ability to apply methods intelligently using the R statistical language


Monday 19 Aug:             Introduction

09:30-10:45      1. Exploratory Data Analysis                           (Prof David Stephenson)
10:45-11:00      Coffee break
11:00-12:00      Interactive R session
12:00-13:00      Lunch
13:00-14:15      2. Probability                                                  (Dr Stefan Siegert)
14:15-15:30      Interactive R session
16:00                Icebreaker at GFI coffee room

Tuesday 20 Aug:            Statistical Modelling

09:30-10:45      3. Statistical Modelling                                    (Prof David Stephenson)
10:45-11:00      Coffee break
11:00-12:00      Interactive R session
12:00-13:00      Lunch
13:00-14:15      4. Statistical Inference                                     (Dr Stefan Siegert)
14:15-15:30      Interactive R session

Wednesday 21 Aug:        Multivariate and Spatial Statistics

09:30-10:45      5. Multivariate Statistics                                   (Prof David Stephenson)
10:45-11:00      Coffee break
11:00-12:00      Interactive R session
12:00-13:00      Lunch
13:00-14:15      6. Spatial Statistics                                           (Dr Stefan Siegert)
14:15-15:30      Interactive R session

Thursday 22 Aug:            Modelling Temporal and Extremal Processes

09:30-10:45      7. Time series modelling                                   (Dr Stefan Siegert)
10:45-11:00      Coffee break
11:00-12:00      Interactive R session
12:00-13:00      Lunch
13:00-14:15      8. Extreme value modelling                               (Prof David Stephenson)
14:15-15:30      Interactive R session and Final Discussion

Useful references

R Language (free download, documentation, etc.)

Lecture notes on basic statistical concepts:

Daniel S. Wilks, Statistical Methods in the Atmospheric Sciences, 3rd edition.

Faraway, J. (2004) Linear Models with R, Chapman and Hall/CRC, 240pp.

Draper NR, Smith H. Applied Regression Analysis (3rd edition). New York: Wiley 1998.

A.C. Davison, Statistical Models, Cambridge University Press 2003.

M.J. Crawley, Statistics: An Introduction Using R, Wiley and Sons 2005.

C. Chatfield, The Analysis of Time-series: An Introduction, CRC press, 6th edition 2003.

C. Chatfield, Time series forecasting, Chapman and Hall/CRC press, 2000.

P. Bloomfield, Fourier Analysis of Time Series: An Introduction (Wiley Series in Probability & Statistics), 2000.

S. Coles, An Introduction to Statistical Modelling of Extreme Values, 224 pages, Springer, 2001.


Advanced Climate Dynamic Courses (ACDC 2019) @ Yosemite Field Station, Yosemite National Park, USA
Sep 22 – Oct 4 all-day

Advanced Climate Dynamics Courses (ACDC), supported by CHESS and other agencies, are yearly summer schools organized by the Bjerknes Centre for Climate Research (University of Bergen) in collaboration with the University of Washington, Woods Hole Oceanographic Institution, and the University of Texas at Austin.

The online application for ACDC 2019 is now open. The summer school will take place at Yosemite Field Station, Yosemite National Park, USA | 22. September – 4. October, 2019. The topic is “The Anthropocene”.

Read the flyer here.

ACDC website and registration. Deadline: 1 April, 2019 (registration closed)


Climate science at high latitudes: eScience for linking Arctic measurements and modeling @ Abisko Scientific Research Station, Sweden
Oct 15 – Oct 24 all-day

Coordination: Paul Zieger and Paul Glantz (Stockholm University)
Co-organisers and Lecturers: Michael Schulz (University of Oslo/Meteorologisk Institutt), Ilona Riipinen (Stockholm University) and Antti Lauri (University of Helsinki)
Expected number of participants: 20-25 students, lecturers (5) and assistants (5)
Maximum no. of CHESS participants: 6   *Travel costs of CHESS students will be covered by CHESS*
Credit points: 5

This course aims to teach the next generation of scientists to integrate different eScience tools and infrastructures to achieve a more holistic interpretation of the climate system and its components through model and data analysis. The focus of the course is on the application of eScience tools, but applied to climate and air quality research at high northern latitudes. It is the third part of a series of three two-week graduate courses, open to graduate students and early career scientists from the Nordic countries and Europe.

More details and the registration form (deadline: 15th of August 2019) can be found here:


Writing successful project proposals – From idea to project: Preparing a draft proposal @ VilVite, Thormøhlens gate 51, 5006 Bergen
Nov 13 – Nov 14 all-day

Course leaders: Friederike U. Hoffmann, Research Coordinator at GFI and EU expert evaluator; Nadine Goris, Researcher at NORCE
Time: 13-14 November 2019, 09:00 – 16:30 both days
Credit point: 1 (ECTS)
Maximum number of participants: 12 (participants will be prioritized according to these categories: 1. CHESS member, 2. Member of Bjerknes Center for Climate Research, 3. Participants with own project ideas)
Registration here.  Deadline for registration: 6th October (closed)
Submitted applicant list

Course description

Target group is early career scientists (PhD, Post Doc, young researchers) in climate sciences with little or no experience in proposal writing.

The course will enable you to apply for external funding of your own research. You will learn how to prepare a draft for a successful research project proposal.

Using your own research ideas, you will learn:

– how to plan and structure a draft proposal
– how to develop the different components of the draft proposal
– how to draft a project budget
– where you can apply for funding

The course includes lectures, group work and plenary discussion. During the course, the participants will develop the project ideas of 3 participants into ready-to-use draft proposals.


Summer School on Predictability of Marine Ecosystems, from physical oceanography to fisheries @ University of Cape Town, Cape Town, South Africa
Jan 13 – Jan 21 all-day

Responsible: Noel Keenlyside / UiB, Mathieu Rouault / UCT&Nansen Tutu Centre (ZA)
Max. no. of participants: 5 CHESS students, and 30 students in total. Travel and accommodation costs will be supported for CHESS students.
Credit points: 2 ECTS
Registration: Please send an email to Nilgun Kulan ( to express your interest, stating your nationality, research topic, and project involved.
Deadline: 14 October 2019

Description of course:

Improved climate predictions coupled with marine ecosystem and impact assessment models are needed to reduce uncertainties in the climatic impacts of climate change and to develop appropriate adaptation plans. Towards this goal, the EU H2020 TRIATLAS project, coordinated by UiB, aims to enhance knowledge of the marine ecosystems and how it responds to climatic (and other) pressures in key areas of the Atlantic using existing and pivotal new (physical, biological, societal) observations and state-of-the-art (Earth system, ecological, and socio-economic) models. This ambitious project calls for the training of a new generation of researchers able to work across disciplines and engage with stakeholders, and thereby to address issues related to sustainable development. The summer school gathers a diverse group of students and experts working in these fields to tackle the above goals in an interdisciplinary context.


  • To stimulate a new generation of researchers to work across the research fields of climate, oceanography, marine-ecosystem, fisheries, and societal impacts, through lectures and exercises on theory, observations, and modelling in these fields.
  • To develop communication skills required for bridging the gap between different scientific communities working on a common goal, which in the case of summer school is the sustainable management of human activities in the Atlantic, through structured group works.
  • To increase awareness of the challenges and transdisciplinary research approaches used in stakeholder engagement, through a lecture and a group exercise.
  • Create a lasting inter-institutional network/community on these topics, by being made aware of the All Atlantic Alliance forum of which TRIATLAS is a part.


  • Participants will gain advanced knowledge on available observations and state-of-the-art climate and ecosystem models;
  • Acquire concepts and tools for understanding and carrying out analysis of bio-physical- interactions;
  • Gain skills in working in an interdisciplinary context;
  • Develop international networks and integrate the ever growing All Atlantic Alliance community, which goes beyond scientific actors;
  • Increased Norwegian involvement in research on the tropical and south Atlantic climate, oceanography, marine ecosystem, and fisheries.

Learning modules/structure:

The summer school will consist in 7 days of morning lectures and afternoon student projects and group work. The student activities will consist in the intercomparing of three selected ecosystems by mixed teams of different backgrounds. They will work on preparing a joint student paper on the approaches and challenges to interdisciplinary research of climatic and other pressures on the tropical and South Atlantic marine ecosystem.


Science Communication – Creating Scientific Illustrations @ University of Bergen
Jan 28 @ 09:00 – Jan 31 @ 16:30

Lecturer: Pina Kingman, MScBMC
ECTS: 1 (If you complete the course, you get a diploma stating your participation, the content of the course and the work effort the course has required. You can apply to your home institution for getting the course accepted as ECTS in your degree. They decide if you will get the ECTS for the participation.)
Maximum no. of participants: 20 in total
Registration: please apply before 15 December 2019 with this online form. (registration closed)

Do you want to use illustration as an effective communication tool? Learn the essentials of graphic design and visual communication theory, drawing by hand and drawing digitally during this 4-day course.

Course description:

This course will introduce the theory and method of how to visually represent your scientific research. Being able to translate complex research into information that can be understood by a wide range of audiences is an important skill that will help you throughout your career.

Communicating your work using different methods helps you to think about your work from different perspectives. Not only will this help you understand your own work better, but it will also give you the tools to be able to explain your work to others.

The skills you will learn in this course are highly transferable to any design project you may do in the future.

Through lectures and workshops, we will cover the following:

  • Principles of design and visual communication
  • How to apply these principles to illustration and graphic design, which in turn will inform all visual material you might want to create, including; graphical abstracts, presentation slides, poster presentations, journal articles, graphs, data visualisation, project logos, animations and outreach material.
  • Best practices for poster and slide presentation design
  • Step by step method on how to draw your own research
  • Introduction to sketching by hand
  • Crash course in digital illustration with mandatory pre-course digital tutorials

By the end of the course, you will have practiced the theory and methods discussed in class by creating an illustration of your own research. Taking your ideas from conceptualisation to final digital artwork.

Completing the digital illustration tutorials before the course begins is mandatory. It is important that you come prepared because we are covering a lot of new skills in a short time and it will be beneficial for you if you already have a foundation to work from.

Course Schedule:

Course dates are 28-31 January, from 9:00 to 16:30 each day.

Day 1: 6.5 hrs lectures & workshops, 1 hr lunch
Day 2: 3 hrs lectures & workshops, 1 hr lunch, 3.5 hrs digital illustration
Day 3: 1 hr lecture, 5.5 hrs digital illustration, 1 hr lunch
Day 4: 1.5 hrs digital illustration, 1 hr lunch, 5 hrs student presentation & group feedback

Software used in the course:

  • Adobe Illustrator, for those who have access
  • Gravit, free vector illustration software
    Note: If any students are already familiar with another digital illustration software, then feel free to use this program. But for the sake of time, I will only provide technical support for those using Gravit Designer or Adobe Illustrator.

Student’s will need to bring to the course: Laptop

Before the course starts, students will need to:

  • Download Gravit Designer or Illustrator onto your laptop
  • Do mandatory digital illustration tutorials (to be provided)

Final assessment:

Students will need to present their illustration on the last day of the course and describe one design principle they used in order to solve a visual problem. It will be okay to show “work in progress.”


Pina Kingman in a biomedical illustrator and animator whose work focuses on telling scientific stories in order to disseminate complex research and promote public awareness of science and medicine. She holds a BSc in Cell Biology and Genetics from the University of British Columbia and a MSc in Biomedical Communication from the University of Toronto.


This course is offered as a joint effort of 4 Norwegian research schools: CHESS, DEEP, ForBio and IBA.

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 (registration closed)
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.

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. (registration closed)
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.


Summer school “Glaciers and climate: new inter-disciplinary perspectives to constrain change – past, present and future” @ Hardanger Fjord Lodge, Folgefonna Ice Cap
Aug 31 – Sep 4 all-day

Responsible: Willem van der Bilt & Jostein Bakke (UiB)
International lecturers:
Max. no. of participants: 7 CHESS students (total participants: max. 20)
Credit points: 2 ECTS
Registration form hereDeadline: 31 May
Submitted applicant list

Course description: This Summer School that will help students to advance the potential of archives of glacier-climate change to better predict the societal impacts of the rapidly melting cryosphere. As the world`s largest freshwater reservoir and a major driver of global sea-level rise, this transformation affects the daily lives of millions. Robust adaptation strategies are underpinned by a combination of observations, reconstructions and projections of glacier-climate. However, existing approaches often lack this inter-disciplinary outlook and the associated cross-fertilization of new ideas. This Summer School will help participants to overcome this barrier, innovate their research and strengthen their interpretations by integrating multiple lines of evidence. To help a new generation of lacier-climate scientists embrace more holistic approaches, the week will be filled with a combination of networking, lecturing and field-based learning. To do so in a stimulating yet safe environment, we will bring an international team of experts and students together in a cozy historical setting right next to Norway`s finest natural glacial laboratories: the Folgefonna ice cap.

Learning modules/structure: During this Summer School, we will help participants to

1) build inter-disciplinary collaborations at the start of their career by a. hosting evening networking workshops and b. organizing poster sessions where participants can apply and develop these skills in a safe environment (days 1-2),
2) introduce an array of emerging cross-disciplinary research tools during a. classroom-based master classes to establish a common theoretical framework (days 1-2) and b. field-based practicals to gain hands-on experience (days 3-4), and
3) disseminate findings to generate impact and take part in public discourse by a. involving communication experts (day 4), and b. engaging with local stakeholders on the causes and consequences of glacier-climate change.

We will soon post detailed program updates on:

Learning outcomes: At the end of this course, students will have learnt to
1) effectively network,
2) link interdisciplinary research questions to skills and techniques, and
3) disseminate their work.

Prerequisites: Research with a focus on glaciers and climate. Students should also be willing and able to take part in outdoor activities during the week, prepare a (poster) presentation on their work, and bring a laptop to help carry out exercises for the master classes and practicals.

For additional questions, please e-mail

Introduction to FAIR Data Management for Geoscientists @ Virtual
Sep 8 – Sep 10 all-day

Responsible: Joe LaCasce/UiO, Jochen Reuder/UiB

Target group: PhD students working with data

Credit points:  1 ETCS

Dates:  8-10 September, 9:00-15:30

No. of participants: Unlimited

Registration form here.  (application deadline: 1st September)

Submitted applicant list

Course description:

This course will provide an introduction to the FAIR guiding principles for data management, their specific implementations within geoscience and practical exercises. Practical steps towards Findable, Accessible, Interoperable and Reuseable data are discussed and exercised emphasising the data provider and data consumer perspectives. Practical introductions to the various elements of the FAIR guiding principles are related to concepts of discovery metadata, use metadata, persistent identifiers (e.g. Digital Object Identifiers) and how they help traceability of decisions (e.g. through scientific citation of data), containers for data (e.g. NetCDF), semantics for geoscientific data (glossaries, thesaurus, taxonomies and ontologies) in a interdisciplinary context and related to terminology as a mechanism for scientific collaboration, tools for generating FAIR data (e.g. how to work with Rosetta and other tools for converting data, how to use Python), how to work with FAIR data, how to publish data with the help of data centres, how to publish data with the help of (focusing on discoverability by Google), national structures that facilitate data sharing (e.g. Norwegian Marine Data Centre, Norwegian Scientific Data Network, Norwegian Infrastructure for Research Data), how these are connected and how to work with Data Management Plans that are/or will be required by funding agencies and resources providers (e.g. UNINETT Sigma2). Practical work will be based on students bringing their own data, evaluation of their FAIRness and how to improve FAIRness for these using Rosetta and Python to create NetCDF according to the Climate and Forecast (CF) Convention with Attribute Convention for Dataset Discovery (ACDD) embedded.


At the end of the course, students will know the FAIR guiding principles, best practises of FAIR data within geoscience and practical approaches to achieving FAIR data using Rosetta and Python as well as how to work with data management plans for their future career.

Learning modules/structure:

The first day will be a full day (6 hours) of lectures, introducing different concepts, one day will be for self study where students work their own dataset. Lecturers will be available by Zoom (open room outside lecture hours) and a dedicated Slack channel through the full week to support students. A more detailed outline of the lectures will be provided online, students are required to describe and upload the dataset they will work with. At the end of the course (last day), each student presents the status of FAIRness of their data following the exercises undertaken. This session is scheduled for 5 hours (10 minutes presentation by each student and a longer discussion session).