This is an opportunity to improve volcanic ash dispersal forecasts through enhancing real-time radar remote sensing. Volcanic ash plumes present a global hazard and have led to well-documented multi-billion-dollar disruptions to international air transport. To improve our forecasts of plume dispersal, radar remote sensing could provide real-time measurements for assimilation into plume dispersal models. However, the use of current single-frequency radars is limited, and this project will carry out unique laboratory experiments to develop the potential of using multi-frequency radar. This new approach offers the capability to make unprecedented measurements of volcanic plume characteristics.
The project will combine laboratory experiments with numerical plume modelling to quantify the improvements achievable in plume dispersal forecasts. This will result in a framework for optimising deployment of current and next-generation multi-frequency radars for measuring volcanic plumes. The work will combine theoretical, laboratory experimental and numerical modelling approaches, with a new multi-frequency radar being used to characterize ash radar reflectivity in a laboratory ash-particle fall chamber.
The PhD will draw on expertise in physical volcanology at Lancaster University, radar remote sensing at the University of St Andrews and numerical plume modelling at the University of Cambridge. Laboratory experimental work will be carried out at Lancaster, with additional training at the other sites. Extensive training in laboratory methods and radar remote sensing will be provided. The project offers an exciting interdisciplinary opportunity, at the forefront of radar remote sensing and physical volcanology.
Candidates shall be good honours graduates in appropriate subject areas (e.g. Earth science, physical geography, physical/natural science or engineering), of a recognised university or comparable university, or persons holding equivalent qualifications who show evidence of exceptional ability, or who have demonstrated their ability in graduate studies.
Candidates should have strong interests in laboratory experiments and remote sensing.
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