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Dr Sarah Bentley

VC Fellow

Department: Mathematics, Physics and Electrical Engineering

I graduated from Durham University with an MMath in 2013. After about in a year in industry working on a geometry system which underlies computer aided design software, I began a PhD at the University of Reading in 2015. As part of the space weather group inside the Meteorology depatrment, the focus of this work was to understand and predict the driving of magnetosphere-scale ULF waves by the solar wind in order to use in space weather models. I stayed on at Reading as a post-doctoral researcher in order to further this work and in 2020 joined Northumbria as a Vice-Chancellor's Fellow. In addition to continuing the various directions of my research, this provides me with the opportunity to develop my teaching and research proposal writing skills.

Due to my mixed backgrounds in space physics, meteorology, maths and geometry, I have a wide range of interests. My primary focus is still the prediction of ULF waves and the resulting radial diffusion in Earth's radiation belts. However, I am also investigating machine learning, optimisation and stochastic/probabilistic approaches to this problem, and how geometric structures combined with data assimilation can be used to efficiently model geomagnetic phenomena that underpin the co-ordinate systems used in space weather prediction.

For more information about me and my work, please visit my personal page.

Sarah Bentley

I currently study the effect of ultra-low frequency (ULF) magnetospheric plasma waves on the Earth’s radiation belts, creating empirical models to characterise these waves and investigating the theory determining their interaction with radiation belt electrons. My two long-term goals relate to our understanding of these waves and their effects, and also to developing mathematical techniques to address some of the data analysis difficulties specific to space
physics (correlation, causality, observation sparsity). Together, these two goals represent some the current limits to space weather forecasting.

  • Please visit the Pure Research Information Portal for further information
  • Imaging the magnetosphere-ionosphere system with ground-based and in-situ magnetometers, Murphy, K., Bentley, S., Miles, D., Sandhu, J., Smith, A. 2022, Magnetospheric Imaging, Elsevier
  • RAS Specialist Discussion Meeting report, Coxon, J., Aruliah, A., Bentley, S., Shore, R. 1 Feb 2022, In: Astronomy & Geophysics
  • Temporal variability of quasi-linear pitch-angle diffusion, Watt, C., Allison, H., Bentley, S., Thompson, R., Rae, I., Allanson, O., Meredith, N., Ross, J., Glauert, S., Horne, R., Zhang, S., Murphy, K., Rasinskaitė, D., Killey, S. 13 Oct 2022, In: Frontiers in Astronomy and Space Sciences
  • Pro-L* - A Probabilistic L* mapping tool for ground observations, Thompson, R., Morley, S., Watt, C., Bentley, S., Williams, P. 20 Feb 2021, In: Space Weather
  • The implications of temporal variability in wave‐particle interactions in Earth's Radiation Belts, Watt, C., Allison, H., Thompson, R., Bentley, S., Meredith, N., Glauert, S., Horne, R., Rae, I. 16 Jan 2021, In: Geophysical Research Letters
  • Particle‐in‐Cell Experiments Examine Electron Diffusion by Whistler‐Mode Waves: 2. Quasi‐Linear and Nonlinear Dynamics, Allanson, O., Watt, C., Ratcliffe, H., Allison, H., Meredith, N., Bentley, S., Ross, J., Glauert, S. Jul 2020, In: Journal of Geophysical Research
  • Random Forest Model of Ultralow-Frequency Magnetospheric Wave Power, Bentley, S., Stout, J., Bloch, T., Watt, C. Oct 2020, In: Earth and Space Science
  • The evolution of inverted magnetic fields through the inner heliosphere, Macneil, A., Owens, M., Wicks, R., Lockwood, M., Bentley, S., Lang, M. 21 May 2020, In: Monthly Notices of the Royal Astronomical Society
  • Capturing uncertainty in magnetospheric ultralow frequency wave models, Bentley, S., Watt, C., Rae, J., Owens, M., Murphy, K., Lockwood, M., Sandhu, J. Apr 2019, In: Space Weather
  • How do Ultra‐Low Frequency waves access the inner magnetosphere during geomagnetic storms?, Rae, J., Murphy, K., Watt, C., Sandhu, J., Georgiou, M., Degeling, A., Forsyth, C., Bentley, S., Staples, F., Shi, Q. 16 Oct 2019, In: Geophysical Research Letters

Kendra Gilmore Deep learning of ground magnetometer networks for space physics Start Date: 01/10/2022

  • PhD July 18 2019
  • Mathematics June 28 2013


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