This PhD project will develop from a well-established field of research for the operations of optical observatories, to address the similar questions that arise for the next generation of radio observatories, such as the SKA, for which the low-frequency component is in Western Australia. The standout science goal of SKA-Low is the detection of the Epoch of Reionisation (EOR), which would confirm the formation of the first stars in the universe and is an exquisite test of cosmology. But the detection of the EOR signal requires observing in the very best of conditions. However, it would be very inefficient to observe just to find out that the conditions had not been optimal and thus have to throw away the data and reobserve.
For efficient use of the precious and costly observatory time, optical and sub-millimetre observatories monitor and predict the coming atmospheric conditions a few days/hours ahead. When the weather is perfect the most important and precise observations are scheduled. This approach needs to be adopted for the next generation radio observatories, which are now being built around the world (SKA-Mid, SKA-Low, ngVLA, LOFAR-2.0, etc). The PhD will take several approaches, all of which promise good results, compare them and identify areas where they might be complementary:
Predictions of Ionospheric weather are now quite sophisticated. This strand will involve comparing the predictions to the observed conditions for the EOR studies. Is one able to analytically predict which are the best days/hours for EOR observations?
Machine Learning of Large Scale Ionospheric behaviour as an alternate method to predict good ionospheric conditions for EoR observations and use that to alter the telescope schedule.
Prediction of Fine Scale structure from the Large scale ionospheric structure is vital, as it is the fine-scale structure that contaminates the data. However, the fine-scale structure is harder to observe and simulate. Can we predict the actual fine-scale structure from the more easily monitored large scale structure? This portion of the Ph.D. could potentially explore the impact and accessibility of ionospheric measurements and simulations more generally.