Dinosaur
A spectral dynamical core for global atmospheric modeling written in JAX.
https://github.com/neuralgcm/dinosaur
Category: Climate Change
Sub Category: Earth and Climate Modeling
Keywords
neuralgcm
Keywords from Contributors
convolutional-neural-network weather jax climate bayesian-methods probabilistic-programming cfd tf-module tensorflow2 python-tensorflow
Last synced: about 22 hours ago
JSON representation
Repository metadata
NeuralGCM's differentiable dycore
- Host: GitHub
- URL: https://github.com/neuralgcm/dinosaur
- Owner: neuralgcm
- License: apache-2.0
- Created: 2023-12-08T14:43:35.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-15T00:17:19.000Z (13 days ago)
- Last Synced: 2025-04-20T08:03:32.972Z (8 days ago)
- Topics: neuralgcm
- Language: Jupyter Notebook
- Homepage:
- Size: 4.61 MB
- Stars: 267
- Watchers: 6
- Forks: 21
- Open Issues: 5
- Releases: 10
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
README.md
Dinosaur: Differentiable Dynamics for Global Atmospheric Modeling 🦖
Authors: Jamie A. Smith, Dmitrii Kochkov, Peter Norgaard, Janni Yuval, Stephan Hoyer
Dinosaur is an old-fashioned (some might say prehistoric) dynamical core for global atmospheric modeling, re-written in JAX to meet the needs of modern AI weather/climate models:
- Dynamics: Dinosaur uses spectral methods to solve the shallow water equations and the primitive equations (moist and dry) on sigma coordinates.
- Auto-diff: Dinosaur supports both forward- and backward-mode automatic differentiation in JAX. This enables "online training" of hybrid AI/physics models.
- Acceleration: Dinosaur is designed to run efficiently on modern accelerator
hardware (GPU/TPU), including parallelization across multiple devices.
For more details, see our paper Neural General Circulation Models for Weather and Climate.
Usage instructions
Dinosaur is an experimental research project that we are still working on
documenting.
We currently have three notebooks illustrating how to use Dinosaur:
We recommend running them using Google Colab with a GPU runtime.
You can also install Dinosaur locally: pip install dinosaur
See also
If you like Dinosaur, you might also like
SpeedyWeather.jl, which
solves similar equations in Julia.
Contributing
See CONTRIBUTING.md for details. We are open to user
contributions, but please reach out (either on GitHub or by email) to coordinate
before starting significant work.
License
Apache 2.0; see LICENSE for details.
Owner metadata
- Name: neuralgcm
- Login: neuralgcm
- Email:
- Kind: organization
- Description:
- Website:
- Location:
- Twitter:
- Company:
- Icon url: https://avatars.githubusercontent.com/u/190404709?v=4
- Repositories: 1
- Last ynced at: 2024-12-04T05:03:56.456Z
- Profile URL: https://github.com/neuralgcm
GitHub Events
Total
- Create event: 35
- Issues event: 3
- Release event: 8
- Watch event: 42
- Delete event: 25
- Issue comment event: 8
- Push event: 116
- Pull request event: 55
- Fork event: 5
Last Year
- Create event: 35
- Issues event: 3
- Release event: 8
- Watch event: 42
- Delete event: 25
- Issue comment event: 8
- Push event: 116
- Pull request event: 55
- Fork event: 5
Committers metadata
Last synced: 7 days ago
Total Commits: 70
Total Committers: 7
Avg Commits per committer: 10.0
Development Distribution Score (DDS): 0.329
Commits in past year: 46
Committers in past year: 4
Avg Commits per committer in past year: 11.5
Development Distribution Score (DDS) in past year: 0.239
| Name | Commits | |
|---|---|---|
| Stephan Hoyer | s****r@g****m | 47 |
| Dmitrii Kochkov | d****v@g****m | 16 |
| Dinosaur authors | n****y@g****m | 2 |
| Jake VanderPlas | v****s@g****m | 2 |
| Rebecca Chen | r****n@g****m | 1 |
| Janni Yuval | j****l@g****m | 1 |
| Ian Langmore | l****e@g****m | 1 |
Committer domains:
- google.com: 7
Issue and Pull Request metadata
Last synced: 2 days ago
Total issues: 12
Total pull requests: 153
Average time to close issues: 11 days
Average time to close pull requests: 2 days
Total issue authors: 4
Total pull request authors: 4
Average comments per issue: 2.17
Average comments per pull request: 0.08
Merged pull request: 81
Bot issues: 0
Bot pull requests: 147
Past year issues: 12
Past year pull requests: 89
Past year average time to close issues: 11 days
Past year average time to close pull requests: 1 day
Past year issue authors: 4
Past year pull request authors: 2
Past year average comments per issue: 2.17
Past year average comments per pull request: 0.01
Past year merged pull request: 68
Past year bot issues: 0
Past year bot pull requests: 88
Top Issue Authors
- shoyer (6)
- sit23 (3)
- whpy (2)
- milankl (1)
Top Pull Request Authors
- copybara-service[bot] (147)
- shoyer (3)
- deven367 (2)
- jeromebarre (1)
Top Issue Labels
- enhancement (6)
- help wanted (6)
- documentation (3)
Top Pull Request Labels
Dependencies
- actions/cache v2 composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- styfle/cancel-workflow-action 0.7.0 composite
- fsspec *
- jax *
- jaxlib *
- numpy *
- pandas *
- pint *
- scikit-learn *
- scipy *
- tree-math *
- xarray *
- xarray-tensorstore *
Score: 7.551712215351311