Leveraging artificial intelligence (AI) to detect weather features, such as atmospheric rivers, fronts, and tropical cyclones, holds great promise in advancing our understanding and prediction of extreme precipitation events. However, to train Artificial Intelligence models effectively, we need a comprehensive database of weather features. In this project, the student will contribute to the development of a comprehensive human-labelled database of atmospheric rivers or/and tropical cyclones and fronts using high-resolution climate model output.
The student will undergo training on how to identify atmospheric rivers by visualizing the high-resolution climate model output. Following this, they will employ suitable data labeling software to draw polygons over the identified atmospheric rivers, generating a meticulously labeled dataset.
By creating this database, the student will be contributing to the development of the training samples needed to train AI models to autonomously detect and classify weather patterns.
Supervisors: Dr Sanaa Hobeichi (email@example.com) and Dr Kimberley Reid (firstname.lastname@example.org)
Location: This project can be undertaken at UNSW or Monash University.