OWZ events
Storm or disturbance event tracks used to define seed points and temporal windows.
Climate AI
Learning from spatio-temporal meteorological tensors before cyclone formation, with a focus on what separates developing and non-developing systems.
Problem
Tropical cyclone genesis involves complex environmental and dynamical changes. A useful model should not only predict whether a disturbance develops, but also help reveal the latent structure that separates developing systems from non-developing ones.
The research goal is to build representations of pre-genesis meteorological tensors and inspect how latent directions correspond to intensification, organisation, moisture, circulation, or other physically meaningful patterns.
Data
Storm or disturbance event tracks used to define seed points and temporal windows.
Reanalysis variables extracted around event-centred spatial windows.
Multi-level atmospheric channels across standard pressure levels.
Temporal movie-like input for MixtureBetaVAE3D-style modelling.
Pipeline
Tensor concept
Scientific questions
Latent structure may reveal environmental patterns associated with genesis.
Temporal latent trajectories can show whether development signals emerge before declaration.
Generated fields should preserve meteorological plausibility while varying relevant factors.
Next
The projects page includes a placeholder for the tropical cyclone tensor builder and HPC workflow.
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