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https://github.com/chilipp/psyplot-ks-seminar-20240201
Presentation of psyplot on the KS Seminar on February 1st, 2024
https://github.com/chilipp/psyplot-ks-seminar-20240201
Last synced: 13 days ago
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Presentation of psyplot on the KS Seminar on February 1st, 2024
- Host: GitHub
- URL: https://github.com/chilipp/psyplot-ks-seminar-20240201
- Owner: Chilipp
- License: cc-by-4.0
- Created: 2024-01-31T12:12:50.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2024-04-04T09:54:10.000Z (8 months ago)
- Last Synced: 2024-10-11T09:28:55.077Z (about 1 month ago)
- Language: Jupyter Notebook
- Size: 47.1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
README
# Using psyplot for visualizing unstructured data and vertical transects
KS Seminar
February 1st, 2024
Philipp S. Sommer
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Chilipp/psyplot-KS-Seminar-20240201/main?filepath=psyplot-framework-presentation.ipynb)
This presentation demonstrates the most recent features of Psyplot, a powerful tool for visualizing climate data on unstructured grids. The utilization of UGRID conventions has become paramount in handling unstructured grids effectively. This presentation demonstrates how psyplot can be used to effectively and straightforwardly to visualize climate data conforming to UGRID conventions, highlighting its role in enhancing the comprehension of spatial and temporal patterns.
Another key focus of the presentation is on the grid-independent extraction of vertical transects in 4-dimensional data, addressing a critical challenge in climate science. I will showcase the new innovative methodologies within Psyplot that facilitate seamless extraction of vertical profiles across varying grid structures, enabling researchers to analyze and interpret climate variables with unprecedented precision. By showcasing practical applications and case studies, the presentation aims to demonstrate the usefullness of psyplot for climate data analysis and model development. Attendees will gain valuable insights into the potential of Psyplot and its role in pushing the boundaries of visualizing climate data on unstructured grids.
## About this presentation
This presentation uses material from
[the presentation at the DACH 2022 conference][DACH2022]. Some parts have been
shown interactively in the GUI during the presentation.[DACH2022]: https://github.com/Chilipp/psyplot-DACH2022-presentation
## Note
This presentation is a jupyter notebook presented with [RISE][rise]. You can
access the raw notebook at
[psyplot-framework-presentation.ipynb](psyplot-framework-presentation.ipynb).You can also execute the cells in this presentation interactively by clicking
on[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/Chilipp/psyplot-KS-Seminar-20240201/main?filepath=psyplot-framework-presentation.ipynb)
## License
The contents of this repository is published under the Creative Commons
Attribution 4.0 International Public License (CC BY 4.0).See the [LICENSE](LICENSE) file for more details.
Copyright (c) 2022-2024, Helmholtz-Zentrum hereon GmbH