AI Weather Quest Python Package
To support participants in the AI Weather Quest, a dedicated Python package has been developed. This package enables users to submit forecasts, access potential training datasets, and perform local forecast self-evaluation.
Comprehensive documentation for the package is available here: AI Weather Quest Python Package Documentation
As the AI Weather Quest is a cutting-edge and evolving competition, regular updates to the package are anticipated. This page provides an up-to-date overview of all changes, improvements, and enhancements to ensure participants have the latest tools at their disposal.
Latest updates
To upgrade the python package, please use the following command:
python3 -m pip install --upgrade AI-WQ-package
| Package Version | Release Date | Summary of updates |
|---|
| 3.0.0 | 11th Aug 2025 | - Public release for start of competition phase.
- Slight update to colorbar when visualising forecast to match AI Weather Quest forecast portal (forecast_plotting.create_colormap).
|
| 2.4.4 | 28th July 2025 | - New function: forecast_submission.AI_WQ_check_submission to verify forecast submission success.
- Excluded grid points from RPS calculation where all quintile climatologies are zero (i.e., dry regions).
- Applied land-sea mask for grid points with less than 50% land coverage. Originally mask was applied for grid points with less than 80% land coverage.
- Separated latitude weighting and global mean computation in RPS calculation.
- Extended ERA5-based training data availability to up to 4 months prior to the current date. Originally only up to 2024.
- Enabled download of historical quintile climatologies at a daily resolution. Originally only for every Monday start date.
- Added functionality to evaluate forecasts for selected geographic regions to enable regional evaluation.
- Implemented a check to exclude submissions from withdrawn teams.
|
| 2.0.0 | 6th May 2025 | Initial public release prior to the JJA (June to August) testing period. |