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 (firstname.lastname@example.org) 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.
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.
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.
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 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 https://www.adobe.com/ca/products/illustrator.html
- Gravit, free vector illustration software https://www.designer.io/en/
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)
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.
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 (http://jmlilly.net/software). Course notes are available online at http://jmlilly.net/course (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.
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.
Responsible: Willem van der Bilt & Jostein Bakke (UiB)
Max. no. of participants: 7 CHESS students (total participants: max. 20)
Credit points: 2 ECTS
Registration form here. Deadline: 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: glacierclimateCHESS.mystrikingly.com.
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 email@example.com
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)
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 schema.org (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.
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).
course responsible: Michael Schulz (UiO/MetNo) and Paul Zieger (SU)
No. of credits: 5 ECTS
Max no. of participants: 6 CHESS students (25 in total)
Course fee and travel will be supported for CHESS participants.
Please go to the course webpage for more details and registration. (Deadline:15 September)
Responsible: Marvin Kähnert, Nadine Steiger, Sonja Wahl (UiB)
Credit points: 1 ETCS
Max no. of participants: 20
Registration deadline: 9 October, 2020
Registration form is here.
Participant submission list
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 be held at the geophysical institute at UiB. For the bigger part of the lectures, the expert will be present whereas the international lecturers will be giving virtual lectures for the students in the classroom.
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