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AI Weather Quest (AI-WQ-package)

Disclaimer: This package is provided for research and competition participation purposes only. It is not intended for use in any operational or production context. It is not an officially supported ECMWF software product.

Overview

AI-WQ-package is a Python library that supports participation in the ECMWF AI Weather Quest, a competition to develop and evaluate AI-based sub-seasonal forecasts.

The package enables you to:

  • Submit forecasts to the AI Weather Quest competition.
  • Evaluate sub-seasonal forecasts using tools developed by the AI Weather Quest team.
  • Download training data for developing sub-seasonal forecast models.

It builds on xarray for efficient NetCDF-based data handling.


Installation

To install the AI-WQ-package on Linux, run the following command:

python3 -m pip install AI-WQ-package

For guidance on installing Python 3 or pip, refer to the official documentation.


Dependencies

The AI-WQ-package requires the following dependencies:

  • numpy (version 1.23 or higher)
  • xarray (version 2024.09.0 or higher)
  • dask (version 2024.9.0)
  • pandas (version 2.2.3 or higher)
  • scipy (version 1.14.1 or higher)
  • netCDF4 (version 1.7.2 or higher)
  • requests (versions 2.32.2 or higher)
  • matplotlib (versions 3.8 or higher)
  • cartopy (versions 0.22 or higher)

If these dependencies conflict with your current working environment, consider installing the package in a new virtual environment.


Upgrading the Package

To upgrade to the latest version, run:

python3 -m pip install --upgrade AI-WQ-package

This project is being actively developed. New updates may be released periodically with detailed annoucements given on the ECMWF-hosted forum.


Software Maturity

Attribute Status
Maturity Static Badge
Support level Best effort — no guaranteed response time
Operational use Not suitable for operational use

License

This project is licensed under the Apache License 2.0. See the LICENSE file for the full text.


Support

This package is not officially supported by ECMWF. Community contributions and questions are welcome via GitHub Issues on the upstream repository or on the ECMWF Community Forum.

For general ECMWF-related enquiries, please use the ECMWF Service Desk.


Documentation

Full documentation is available on ReadTheDocs:

https://ecmwf-ai-weather-quest.readthedocs.io/en/latest/

Metadata

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