Training Description
Learners are introduced to climate data analysis using satellite-based datasets from the Climate Change Initiative (CCI) through this hands-on training, originally held at the Adaptation Futures Conference (AF2025) in New Zealand. Designed for beginners with no prior experience in Python or climate data analysis the session provides a step-by-step guide to exploring climate trends and assessing climate risk exposure.
Using a Jupyter Notebook we guides learners through a real-world example focusing on New Zealand’s 2019 heatwave, using climate data to highlight how high temperatures and dense population areas intersect to produce risk hotspots. By the end of the training, participants will gain practical skills to explore climate hazards, visualise climate trends, and assess potential human impacts.
Training Objectives:
- Access ESA CCI Essential Climate Variables (ECVs) using the CCI Toolbox in Python
- Navigate and subset climate datasets using xarray
- Compute and visualise climate variables such as Land Surface Temperature (LST) using Matplotlib
- How to save the results for further analysis.
- How to map and interpret ECVs changes over time and space
Training Material
To follow along with the training, you can view the Jupyter Notebook in read-only format below. To interact with or modify the content, you can fork the repository from the GitHub page or download the notebooks to your local environment.
You can also access the Notebook from the ESA CCI Training Environment using the following link:
Useful Links