Machine Learning for Climate and Weather Community Working Group

The Machine Learning for Climate and Weather Working Group includes researchers from several Australian universities and research institutions who use and co-develop the Australian Community Climate Earth System Model (ACCESS) for their research.

How to join a Community Working Group

Machine learning for Climate and Weather WG Home

Click on the Machine Learning for Climate and Weather WG Home button above to follow this working group mailing list, information about events and meetings and activity reports.

The main aims of this group are:

  • To facilitate mutually-beneficial collaborations between climate/weather scientists and ML experts.
  • To create a platform for knowledge exchange where ACCESS-NRI, NCI, the climate community and ML experts share insights, data, and methodologies to accelerate progress in both fields.
  • To advise ACCESS-NRI, NCI and the climate community on advances in ML in climate/weather science and techniques and their impact on future directions in climate/weather research (e.g. modelling, resourcing etc.).
  • To ensure that the Australian community remains at the forefront of the use of ML/AI in research and applications in weather and climate.
  • To contribute to the training of climate/weather scientists in applying ML to their research (through organised events/ resource sharing).
Co-Chairs:

Sanaa Hobeichi
Ryan Holmes
Vassili Kitsios
Tennessee Leeuwenburg

ACCESS-NRI Liaison: 

Micael Oliveira

 

Community Working Groups Terms of Reference