Location: The University of Melbourne and Bureau of Meteorology

Time: February to July 2020

Atmospheric turbulence represents a significant aviation hazard, causing damage to aircraft and injury to passengers and crew (click here to see a recent story). Detection of turbulence and accurate prediction of its occurrence remain significant challenges for aviation weather forecasters. Numerical weather prediction models are typically run at resolutions that are too coarse to explicitly represent the turbulence that is relevant to aircraft motions.

Since becoming operational in 2015, the unprecedented high spatiotemporal resolution Himawari-8 geostationary satellite has opened new opportunities to observe atmospheric turbulence. Newly developed diagnostic techniques have been developed to identify these turbulent regions from satellites. Application of these techniques provides a promising approach to improve turbulence monitoring and forecasting, ultimately enhancing aviation safety.

The proposed project aims to implement this new turbulence diagnostic scheme and evaluate its performance using high-resolution Himawari-8 imagery. Using data from the aviation industry, some preliminary verification of the diagnostic will be undertaken. Additional observational and model data will be used to investigate turbulence-prone atmospheric conditions and processes (e.g. wind shear, mountain waves, etc.). Possible pathways to refinements to the diagnostic will be explored.

Requirements: Some programming experience with a data analysis and visualisation language such as Python, Matlab, or IDL is a requirement.