
awesome-weather-models
🌦️ A catalogue and categorization of AI-based weather forecasting models.
Stars: 99

A catalogue and categorization of AI-based weather forecasting models. This page provides a catalogue and categorization of AI-based weather forecasting models to enable discovery and comparison of different available model options. The weather models are categorized based on metadata found in the JSON schema specification. The table includes information such as the name of the weather model, the organization that developed it, operational data availability, open-source status, and links for further details.
README:
A catalogue and categorization of AI-based weather forecasting models.
This page provide a catalogue and categorization of AI-based weather forecasting models. The aim is that this page will enable discovery and comparison of the different available model options.
The weather models are categorized according metadata found in the JSON schema specification (schema_ai_models.json). The table below (in alphabetical order) is extracted from the full categorization with columns defined as:
- Name: Name of the weather model.
- Organization: Organization that developed the weather model.
- Operational Data: If forecast data from the model is provided at an operational basis.
- Open Source: If the source code is provided as open source.
- Open Weights: If the model weights are provided as open weights.
Click the link of the model name to see the full model categorization.
Name | Lead Organization | Operational Data | Open Source | Open Weights | Links |
---|---|---|---|---|---|
AIFS |
ECMWF | âś… CC BY 4.0 |
❌ | ❌ | [paper], [access] |
ARCHESWEATHER‑L |
INRIA | ❌ | ✅ MIT |
âś… MIT |
[code], [paper] |
ARCHESWEATHER‑M |
INRIA | ❌ | ✅ MIT |
âś… MIT |
[code], [paper] |
ARCHESWEATHER‑S |
INRIA | ❌ | ✅ MIT |
âś… MIT |
[code], [paper] |
Aurora |
Microsoft | ❌ | ✅ MIT |
âś… MIT |
[code], [paper], [docs], [pypi] |
ClimaX‑H |
Microsoft | ❌ | ✅ MIT |
❌ | [code], [paper], [docs] |
ClimaX‑L |
Microsoft | ❌ | ✅ MIT |
❌ | [code], [paper], [docs] |
FengWu |
OpenEarthLab | ❌ | ✅ MIT |
âś… None |
[code], [paper] |
FourCastNet |
Nvidia | ❌ | ✅ BSD 3-Clause |
âś… BSD 3-Clause |
[code], [paper] |
GenCast |
Google DeepMind | ❌ | ❌ | ❌ | [paper] |
GraphCast |
Google-DeepMind | ❌ | ✅ APACHE-2.0 |
âś… CC BY-NC-SA 4.0 |
[code], [paper], [blog] |
MET Norway |
MET Norway | ❌ | ❌ | ❌ | [paper] |
NeuralGCM‑ENS |
Google Research | ❌ | ✅ Apache-2.0 |
âś… CC BY-NC-SA 4.0 |
[code], [paper] |
NeuralGCM‑H |
Google Research | ❌ | ✅ Apache-2.0 |
âś… CC BY-NC-SA 4.0 |
[code], [paper] |
NeuralGCM‑L |
Google Research | ❌ | ✅ Apache-2.0 |
âś… CC BY-NC-SA 4.0 |
[code], [paper] |
NeuralGCM‑M |
Google Research | ❌ | ✅ Apache-2.0 |
âś… CC BY-NC-SA 4.0 |
[code], [paper] |
Pangu‑Weather |
Huawei | ❌ | ✅ CC BY-NC-SA 4.0 |
âś… CC BY-NC-SA 4.0 |
[code], [paper] |
Prithvi WxC |
IBM and NASA | ❌ | ✅ MIT |
âś… MIT |
[code], [paper], [weights] |
Contributions are much welcome! Make a PR or issue and we will incorporate it. Contributions could for example be:
- Add a model to the list
- Update categorization and links
- Feedback on categorization/structure to make it more useful
When making a PR, follow the these steps to make sure your contribution is consistent with this repo structure:
- All updates/changes should be done to the following files:
-
data_ai_models.json
for updates/changes to model categorization. -
schema_ai_models.json
for schema changes. -
README_no_table.md
for changes to the README.
-
When updates/changes are completed run
python validate_convert_insert.py
. Make sure all JSON validations checks pass. -
The files
ai_model.md
and ´README.md´ will be auto-generated from the script. -
Add all the changed and generated files and submit the PR.
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