Scientific writing course with Daniel Soule @ Geophysical Institute, University of Bergen, Bergen
Oct 23 – Oct 25 all-day

Three days intensive course tailored for climate science, led by Daniel Soule.

Credit points: The workload is three full days with teaching and exercise and corresponds to 1 ECTS.

Maximum no. of participants: 20

Register here. (closed)

Submitted application list

Course description:

This three day writing workshop will introduce students to complexities of writing research papers, with a view to making the process easier and more transparent. Day one will concentrate on three interrelated problems in writing research: mastering the style of a scientific research paper; how to be an efficient writer and understand how and why writers get blocked; and finally tips for reviewing the literature and developing critical thinking.

Day two breaks down the research paper into its constituent parts and unpick their structures. These structures can then be used to model a plan and write the article.  Finally, day three takes an overview of the whole process of writing and publishing a research paper, including co-authoring, drafting, editing, and peer review. Importantly, this final day will also discuss the importance of the post-publication life of your papers, such as their impact and social networking your results.

Program schedule (all lectures at 4/F lecture room, West Wing, Geophysical Institute, University of Bergen):

Day 1: Introduction to Research Writing:

10:00- 10:30 Introductions, course outline, learning objectives
10:30- 11:30 Academic style
11:30- 11:45 Coffee break
11:45- 12:45 Academic style
12:45- 13:30 Lunch
13:30- 14:45 The Writing Process: Generating Writing
14:45- 15:00 Coffee break
15:00- 16:00 Reviewing the Literature and Thinking Critically

Day 2: Research Articles Structures

10:00- 11:30 How to Write Introductions, Conclusions & Discussions
11:30- 11:45 Coffee break
11:45- 12:45 How to write Introductions, Conclusions & Discussions
12:45- 13:30 Lunch
13:30- 14:45 Writing About Evidence and Data
14:45- 15:00 Coffee break
15:00- 16:00 How to Write Methodologies

Day 3: Writing for Different Audiences

10:00- 11:30 The Writing Process: Co-authoring, Editing and Proofreading
11:30- 11:45 Coffee break
11:45- 12:45 Submission and Peer-review
12:45-13:30 Lunch
13:30-14:45 The Publishing Process
14:45-15:00 Coffee break
15:00-16:00 Maximizing Your Impact: Impact Factors, H Indexing and Social Networking



Hydrometeorological downscaling and bias correction techniques @ Statkraft AS, Oslo, Norway
Nov 6 – Nov 8 all-day

Course responsible: Prof. Asgeir Sorteberg, Geophysical Institute, UiB and Prof. John Burkhart, Department of Geosciences, UiO

Instructors: Rasmus Benestad, MET Norway and Ethan Gutmann, National Center for Atmospheric Research (NCAR)

Target Group: Doctoral students with hydrological, meteorological, or climatological background with an interest in regional atmospheric and hydrological downscaling and bias correction methods.

Credits: 1 ECT credits.

No. of participants: Max 15 students; 7 CHESS PhD students and 8 non-CHESS participants.

Registration here.

Submitted participant list

Background: Downscaling and bias correction are important steps in the processing data for the development of hydrometeorological forcing datasets for impact analyses of climate. Renewable energy forecasting, geo hazard warning, climate mitigation, and numerous other impact studies require downscaled or bias corrected data as forcing data to drive models. Presently a wide variety of techniques are in use. Each of the specific fields requires an understanding of the driving geophysical conditions, but also requires a high degree of specialization. A short course on hydrometeorological downscaling and bias correction techniques is offered to provide an improved foundation for students working in these fields.

Course objectives: The course will guide in the development of competence for a new generation of researchers and characterize the strengths and weaknesses of different hydrometeorological downscaling and bias correction approaches. Specifically, the course will provide an overview of the  application of statistical and dynamical approaches to downscaling and bias correction. Students will be introduced to the `esd` package in R that is widely in use for statistical downscaling and the Intermediate Complexity Atmospheric Research (ICAR) model that provides a quasi-dynamical approach to downscaling. Theoretical and practical background to statistical and dynamic approaches will be covered and assessed for applicability in varying use cases. This is a unique opportunity to gain instruction of the two software packages provided by their authors.

Outcomes: Participants will gain advanced knowledge on statistical, dynamical and pseudo dynamical downscaling and their role in providing relevant information for different applications. Following they will obtain:

  1. knowledge regarding different downscaling and bias correction techniques
  2. critical ability to assess and characterize the main challenges with the different approaches
  3. practical introduction to the `esd` package and the ICAR model, and knowledge of how to critically judge the outcome of different techniques and their usability for various applications.

Learning module: The course will consist of 3 full-day lectures and practical modelling exercises, followed by a project due 1 month after the course.  Attendants are expected to allow at least two days to prepare for the course. Students will use their own laptops and will be required to test software installations prior to arrival. Further, they are to read relevant literature from a provided reference list before arrival. The final project will be due 1 month following the course. It is beneficial for students to work with their own ‘case’ and datasets. Optimally, students will have these data available to work with during the course practicals. Further details regarding what type of data to prepare and the software installations will be provided once students have registered.

Course Outline:

Day 1:  Introduction to statistical and dynamical downscaling approaches for climate analyses; Statistical downscaling with `esd`
Day 2:  Dynamical and Quasi-dynamical downscaling with ICAR
Day 3:  The use of bias correction methods in hydrometeorological applications

Prerequisites: Students should have fundamental knowledge of meteorological and climatological processes. Familiarity with bash, linux console, and python or R scripting is helpful.


Writing successful project proposals – From idea to project: Preparing a draft proposal @ Geophysical Institute, University of Bergen, Bergen
Nov 20 – Nov 21 all-day

Course leaders: Friederike U. Hoffmann, Research Coordinator at GFI and EU expert evaluator; Nadine Goris, Researcher at Uni Climate

Time: 20-21 November 2017, 09:00 – 16:30 both days

Credit point: 1 (ECTS)

Maximum number of participants: 14 (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: 29 October

Submitted participant 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.