Studying for Master of Science
Area of study:
Space weather forecasting using Hidden Markov models
Supervisor: Ting Wang
Title: Space weather forecasting using Hidden Markov models
Supervisors: Associate Professor Ting Wang and Dr Matthew Parry
- Bachelor of Science (Hons) in Statistics (University of Otago)
- Bachelor of Science in Statistics (University of Otago)
The study of space weather concerns interactions between the Sun and Earth. Charged particles originating from the Sun entering Earth’s atmosphere (called solar wind) interact with the Earth’s magnetic field - also referred to as Earth’s magnetosphere, which runs thousands of kilometres deep into space. The Earth’s magnetic field provides some protection from solar wind by deflecting the particles or channelling them toward the poles, but when solar wind is strong enough it can lead to perturbations of the magnetic field on the surface of the Earth called geomagnetic storms. This occurs when the interactions cause increased plasma movement and pressure in the magnetosphere, which causes inflation and therefore disturbance of Earth’s magnetic field. When extreme, geomagnetic storms can damage energy infrastructure, causing power outages and danger to human life, so it is of interest to study these storms.
It is of particular interest to categorise the activity of geomagnetic storms to understand the temporal occurrence patterns of storms with different magnitudes. Forecasting large/extreme geomagnetic storms could help prevent/mitigate potential damages caused by these storms. While there has been research undertaken by physicists on geomagnetic storms, little systematic statistical analysis has been completed, despite the large amounts of data available on these phenomena.
This project will contribute to a five year research programme, led by Professor Craig Rodger (University of Otago) and funded by the MBIE Endeavor fund, to develop space-weather prediction and risk mitigation measures for New Zealand's energy infrastructure.