How to work with meteorological ECMWF data
A good starting point how you can work with European Centre for Medium-Range Weather Forecasts (ECMWF) services and data through Python using Jupyter notebooks.
https://github.com/ecmwf/notebook-examples
Category: Sustainable Development
Sub Category: Education
Keywords
ecmwf ecmwf-api magics notebook python visualisation
Keywords from Contributors
grib meteorology bufr
Last synced: about 2 hours ago
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Repository metadata
Example notebooks showing how to work with ECMWF services and data
- Host: GitHub
- URL: https://github.com/ecmwf/notebook-examples
- Owner: ecmwf
- License: apache-2.0
- Created: 2018-10-22T16:36:07.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2025-04-16T11:10:26.000Z (11 days ago)
- Last Synced: 2025-04-20T09:04:05.802Z (7 days ago)
- Topics: ecmwf, ecmwf-api, magics, notebook, python, visualisation
- Language: Jupyter Notebook
- Size: 221 MB
- Stars: 222
- Watchers: 23
- Forks: 78
- Open Issues: 1
- Releases: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
README.md
- How to work with meteorological data
The examples in this space should give you a good starting point how you can work with ECMWF services and data through Python using Jupyter notebooks.
- Visualisation meteorological data using ECMWF's Magics plotting package for meteorological data.
- Download images and reproducing ECMWF Open Charts using new ECMWF Python libraries
Many notebooks that showcase processing of ECMWF data using Metview can now be found in Metview documentation page:
Each notebook has a list of nececary libraries needed for it to work and code to install it.
If you clone this repo and want to explore all the notebooks, you can use the environment.yml file to create a conda environment and install all the libraries inside, using this command:
conda env create -f environment.yml
Note: All the libraries are frozen on 09th January 2025.
Owner metadata
- Name: European Centre for Medium-Range Weather Forecasts
- Login: ecmwf
- Email: [email protected]
- Kind: organization
- Description: Providing software to work with meteorological data and services
- Website: www.ecmwf.int
- Location: Shinfield Park, Reading, United Kingdom
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/6368067?v=4
- Repositories: 44
- Last ynced at: 2023-03-02T03:00:24.789Z
- Profile URL: https://github.com/ecmwf
GitHub Events
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- Delete event: 4
- Push event: 31
- Pull request event: 21
- Fork event: 9
- Create event: 7
Last Year
- Watch event: 25
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- Push event: 31
- Pull request event: 21
- Fork event: 9
- Create event: 7
Committers metadata
Last synced: 6 days ago
Total Commits: 243
Total Committers: 4
Avg Commits per committer: 60.75
Development Distribution Score (DDS): 0.436
Commits in past year: 24
Committers in past year: 1
Avg Commits per committer in past year: 24.0
Development Distribution Score (DDS) in past year: 0.0
| Name | Commits | |
|---|---|---|
| Milana Vuckovic | m****c@e****t | 137 |
| Sylvie Lamy-Thepaut | s****t@e****t | 83 |
| StephanSiemen | s****n@g****m | 20 |
| Iain Russell | I****l@e****t | 3 |
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Issue and Pull Request metadata
Last synced: 1 day ago
Total issues: 4
Total pull requests: 18
Average time to close issues: 24 days
Average time to close pull requests: 6 days
Total issue authors: 4
Total pull request authors: 4
Average comments per issue: 2.0
Average comments per pull request: 0.33
Merged pull request: 16
Bot issues: 0
Bot pull requests: 0
Past year issues: 2
Past year pull requests: 13
Past year average time to close issues: 2 days
Past year average time to close pull requests: 1 minute
Past year issue authors: 2
Past year pull request authors: 1
Past year average comments per issue: 2.0
Past year average comments per pull request: 0.08
Past year merged pull request: 13
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- yuriishizawa (1)
- clausmichele (1)
- erick-otenyo (1)
- basitkhanNZ (1)
Top Pull Request Authors
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- sylvielamythepaut (3)
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Top Issue Labels
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Dependencies
- cartopy
- cdsapi
- cfgrib
- metview-batch
- pip
Score: 6.79346613258001