Climate science at high latitudes: Modeling and model evaluation

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.

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.

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.

Schedule

Setup Download files required for the lesson
00:00 1. Introduction What programs and applications are available for working with Climate data?
00:00 2. Data formats in Climate Sciences What are the main data types used in Climate Sciences?
What are the most common python packages to read/write Climate data?
What format should I use to represent my data?
00:00 3. Intro to Coordinate Reference Systems & Spatial Projection What is a coordinate reference system and how do I interpret one?
Which projection should I use for high-latitudes?
00:00 4. Python for Climate Data How do I find my way with Python and Jupyter notebooks?
How can I manage my projects in Python with Github?
00:00 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.