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WeatherGenerator

A machine learning-based Earth system models that is trained on a wide range of datasets, including reanalyses, forecast data and observations, to provide a robust and versatile model for the dynamics.
https://github.com/ecmwf/weathergenerator

Category: Atmosphere
Sub Category: Meteorological Observation and Forecast

Last synced: about 13 hours ago
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Repository metadata

The repository of the WeatherGenerator project

README.md

The WeatherGenerator project is developing a machine learning-based Earth system model.
It will be trained on a wide range of datasets, including reanalyses, forecast data and observations, to provide a robust and versatile model for the dynamics.
Through this, it can be used for a wide-range of applications.

More details coming soon. Please open an issue if you are interested in using the model.

Owner metadata

GitHub Events

Total
Last Year

Committers metadata

Last synced: 21 days ago

Total Commits: 426
Total Committers: 30
Avg Commits per committer: 14.2
Development Distribution Score (DDS): 0.725

Commits in past year: 426
Committers in past year: 30
Avg Commits per committer in past year: 14.2
Development Distribution Score (DDS) in past year: 0.725

Name Email Commits
Christian Lessig c****g@e****t 117
Timothy Hunter t****r@e****t 70
iluise 7****e 34
Savvas Melidonis 7****l 23
Simon Grasse 1****i 23
Sophie X 2****x 20
Michael Langguth 6****9 17
Julian Kuehnert J****u 13
Kacper Nowak k****k@a****e 13
Julius Polz 5****z 12
kctezcan k****n@g****m 12
Seb Hickman 5****0 10
Matthias Karlbauer m****r@e****t 9
Javad kasravi k****6@g****m 6
Moritz Hauschulz 6****z 6
Simone Norberti 6****n 6
Sorcha Owens 7****w 6
Till Hauer t****l@w****e 6
Sindhu-Vasireddy 9****y 5
Jifeng Wang w****a@1****m 4
Michael Tarnawa 1****r 3
ankitpatnala a****a@g****m 3
Bart Schilperoort b****t@g****m 1
Belkis Asma SEMCHEDDINE s****a@y****r 1
Ed Wiebe e****e 1
Tiago Quintino t****o@g****m 1
Wael w****5@g****m 1
jehangirawan 8****n 1
rushchanskii 1****i 1
yperugachidiaz 5****z 1

Committer domains:

Issue and Pull Request metadata

Last synced: 2 months ago

Total issues: 581
Total pull requests: 496
Average time to close issues: 18 days
Average time to close pull requests: 6 days
Total issue authors: 27
Total pull request authors: 26
Average comments per issue: 1.49
Average comments per pull request: 1.11
Merged pull request: 286
Bot issues: 0
Bot pull requests: 0

Past year issues: 581
Past year pull requests: 496
Past year average time to close issues: 18 days
Past year average time to close pull requests: 6 days
Past year issue authors: 27
Past year pull request authors: 26
Past year average comments per issue: 1.49
Past year average comments per pull request: 1.11
Past year merged pull request: 286
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/ecmwf/weathergenerator

Top Issue Authors

  • clessig (149)
  • tjhunter (78)
  • shmh40 (41)
  • iluise (41)
  • mlangguth89 (37)
  • kctezcan (35)
  • kacpnowak (29)
  • grassesi (24)
  • ankitpatnala (20)
  • jpolz (19)
  • SavvasMel (17)
  • Jubeku (17)
  • MatKbauer (14)
  • javak87 (12)
  • sophie-xhonneux (12)

Top Pull Request Authors

  • clessig (97)
  • tjhunter (74)
  • iluise (38)
  • kacpnowak (31)
  • grassesi (30)
  • mlangguth89 (26)
  • kctezcan (25)
  • shmh40 (21)
  • jpolz (20)
  • javak87 (19)
  • SavvasMel (19)
  • sophie-xhonneux (19)
  • Jubeku (13)
  • Sindhu-Vasireddy (10)
  • MatKbauer (9)

Top Issue Labels

  • enhancement (235)
  • bug (167)
  • model (87)
  • datasets (75)
  • infra (70)
  • evaluation (50)
  • initiative (25)
  • science (21)
  • quality (10)
  • good first issue (10)
  • data reading (9)
  • performance (8)
  • eval (8)
  • documentation (5)
  • app (3)
  • question (3)
  • inference (3)
  • needs-design (2)
  • proj:raina (1)
  • proj:hclimrep (1)

Top Pull Request Labels

  • enhancement (25)
  • bug (21)
  • datasets (18)
  • model (16)
  • evaluation (12)
  • infra (8)
  • quality (3)
  • eval (1)
  • data:reading (1)

Dependencies

pyproject.toml pypi
uv.lock pypi
  • 103 dependencies
packages/dashboard/pyproject.toml pypi
  • boto3 <1.36
  • mlflow ~=3.3.2
  • plotly ~=6.1.2
  • polars ~=1.30.0
  • requests ~=2.32.4
  • streamlit ~=1.46.0
  • streamlit-authenticator >=0.4.2
  • watchdog *
  • weathergen-common *
  • weathergen-metrics *
.github/workflows/issue_assign.yml actions
packages/metrics/pyproject.toml pypi
  • mlflow-skinny *
  • weathergen-common *
.github/workflows/ci.yml actions
  • actions/checkout v4 composite
  • astral-sh/setup-uv v5 composite
.github/workflows/issue_set_label.yml actions
  • actions/github-script v7 composite
packages/common/pyproject.toml pypi
  • astropy-healpix ~=1.1.2
  • dask >=2024.9.1
  • numcodecs <0.16.0
  • omegaconf ~=2.3.0
  • pyyaml *
  • xarray >=2025.6.1
  • zarr ~=3.1.3
packages/dashboard/uv.lock pypi
  • 129 dependencies
packages/evaluate/pyproject.toml pypi
  • cartopy >=0.24.1
  • earthkit-data ==0.18.2
  • eccodes ==2.44.0
  • eccodeslib ==2.44.0.7
  • eckitlib ==1.32.3.7
  • omegaconf *
  • panel *
  • plotly >=6.2.0
  • seaborn *
  • weathergen-common *
  • weathergen-metrics *
  • xhistogram *
  • xskillscore *
packages/readers_extra/pyproject.toml pypi
  • weathergen-common *
  • xarray *
  • zarr *
.github/workflows/pr_assign_labels.yml actions
  • actions/github-script v7 composite

Score: 9.284519770150434