Challenge 10 -Climate intelligence: from data to visualization

[EsperanzaCuartero]

Challenge 10 - Climate intelligence: from data to visualization

Stream 1 - Software Development for Earth Sciences

Goal

Develop a Jupiter notebook with Python code to produce data and graphics used in the climate intelligence reports, present as training material.

Mentors and skills

• Mentors: Edward Comyn-Platt, Iryna Rozum
• Skills required:
  • Python
  • Git
  • Knowledge of meteorological datasets would be an advantage

Note: Only nationals from European Union (EU) Member States and countries associated with EU’s Space Programme (currently Iceland and Norway) are eligible to participate (see Terms and Conditions).

---

Challenge description

Currently, all data and graphics are produced using ECMWF tools, which are not available for general users and the results cannot be reproduced in the CDS Toolbox.
The solution could be to develop a set of codes to retrieve data and produce graphics using the new cads-toolbox Python package. Create a Jupiter notebook with training material for users.

Regarding the data/systems to use: Copernicus climate data store (CDS), CDS-API for data retrieval, the cads-toolbox Python package for data processing and visualisation, other Python packages, GitHub.

Ideas for the implementation

• Install CDS-API and cads-toolbox Python package
• Download selected ECVs for the Copernicus C3S climate data store using CDS-API, calculate ECVs not available from the CDS
• Explore the content of data files
• Preprocess variables where needed by applying masking over land or ocean, perform units conversion where needed
• Calculate anomalies
• Produce visualisation based on examples from https://climate.copernicus.eu/climate-bulletins
• Create a Jupiter notebook with training material based on examples

[trakasa]

... you can ask questions on the challenge here...

[ameyabp]

I am a PhD student from the University of Washington, Seattle, USA. The description says that the competition is not open for students from the US. Can we do something about it?

[IrynaRozum]

Yes ECV = Essential Climate Variables.

[nicrie]

In the challenge description it reads that the cads-toolbox Python package [should be used] for data processing and visualisation. From checking the cads-toolbox it seems that there are plans to make preprocessing (e.g. computing climatology) possible, but they are not yet implemented. Perhaps there will be an update in the near future making these features available but I could not find information on that.

Question: is the desired outcome of this challenge to create tutorials/data visualizations using preprocessing/viz features provided by cads-toolbox, or rather our own by-hand implementations using xarray, matplotlib, seaborn, cartopy etc.?

[IrynaRozum]

The challenge is to use cads-toolbox where possible, if some functions are not available, then other python packages can be used. Climatology and anomalies can easily be calculated using xarray.

[nicrie]

thanks @IrynaRozum for the quick feedback! Looking closer at the current main branch it seems that only retrieve is implemented, so apart from downloading data I cannot identify other actions currently available in cads-tools. We'll use other packages then :)