E-science tools for climate research - Climate science at high latitudes: Modeling and model evaluation
Context:
This course aims to teach in a Nordic framework 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 second part of a series of three two-week graduate courses, open to Nordic graduate students and early career scientists, developed originally within the education program of the Nordic Centre of Excellence eSTICC (eScience Tools for Investigating Climate Change at High Northern Latitudes).
The course is supported by Nordforsk (Nordic eScience Globalisation Initiative; NeGI), the University of Oslo (course GEO4990), eSTICC, Bolin Centre for Climate Research and the CHESS Research School.
Practical work:
Students are asked to cooperate in small groups (2-3) with an assistant on individual subjects of interest in the realm of climate model evaluation and analysis. Jupyter notebooks shall be compiled to document the work and results. Two Presentations are expected during the course to report on progress.
The learning outcomes:
In the end of the course the student will have
- skills to set up small python based data analysis projects;
- knowledge about existing online databases containing atmospheric and ecosystem data;
- the ability to understand and evaluate model output;
- increased skills to visualize data;
Some of the transferable skills the course strives to improve:
- statistical analysis of model and field measurements;
- multidisciplinary approach;
- project management; and
- collaborative learning.
Prerequisites:
The participants are expected to be able to write scripts using a structural programming language (e.g. Python, R or MATLAB). Basic data analysis skills are also expected. The main programming language to be used on the course will be Python. The main tool for visualization and online publishing will be Jupyter Notebook.
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- Diego Aliaga
- Jonas Gliss
- Anne Fouilloux
A list of contributors to the lesson can be found in AUTHORS
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