Dr. Ben Reid
School of Engineering
Assistant Professor
Address
Engineering Building
University of Birmingham
Birmingham
B15 2TT
UK
Ben is an expert in space environment data assimilation, particularly in the development of particle filters for operational space weather modelling. Ben's research focuses on using the maximum amount of available information from highly non-linear and time-dependent measurements.
Ben has developed (and maintains) several operational real-time space weather models, including A-CHAIM and AIDA.
B.Sc. (Hon. Physics, Mathematics) University of New Brunswick 2015
Ph.D. (Physics) University of New Brunswick, 2024
Ben did an undergraduate degree with honours (B.Sc.) at the University of New Brunswick in 2015 with a double major in Physics and Mathematics. His undergraduate honours project, supervised by Dr. Abdelhaq Hamza, examined the behaviour of financial markets as a reduced-dimension thermodynamic system. During this time he also spent several summers working with CERN working with Monte Carlo methods, statistical inference, and high performance computing (HPC).
After several years Ben returned to the University of New Brunswick to complete a Ph.D in Physics in 2024, under the joint supervision of Dr. P. T. Jayachandran and Dr. David Themens. His graduate research led to the development of the Assimilative Canadian High Arctic Ionospheric Model (A-CHAIM), the first operational space weather model to use a particle filter. A-CHAIM includes a F-layer model which assimilates data from Global Navigation Satellite Systems (GNSS), ionosondes, and satellite altimeters. It also includes auroral and Solar Energetic Particle (SEP) data assimilation sub-models. A-CHAIM is able to produce a near-real-time ionospheric specification and short-term forecast while running on a modest workstation, or high-performance laptop computer. Coincidentally, these are the same hardware requirements needed to open the PDF of the overly long dissertation describing A-CHAIM.
The success of A-CHAIM led directly to the development of AIDA, a real-time global ionosphere/plasmasphere model. This model runs on the BlueBEAR HPC at the University of Birmingham, and produces a full 3D representation of the ionosphere using data streamed from over 2000 GNSS receivers worldwide.
Ben's research is focused in a few main areas.
Ben has developed (and maintains) several operational real-time space weather models, including A-CHAIM and AIDA. These models use Monte Carlo ensembles to resolve uncertainty in the ionospheric state, and so rely on techniques such as dimension reduction to efficiently search the state space. Ben is also interested in techniques to adaptively model the variability of a partially observed system, and to perform efficient autonomous instrument calibration and measurement error determination. These models rely heavily on Total Electron Content (TEC) measurements from GNSS receivers, which are integrated, non-local, non-linear, noisy, and biased measurements. To use all available information from these measurements requires careful consideration, and novel techniques.
Ben is also interested in how data assimilation models can be coupled together, to allow for localized grid refinements and to feedback information to improve physical drivers.
Finally, Ben is also investigating how particle filters can be used to model other components of the space weather environment, such as the density and composition of neutral atmosphere (thermosphere) and the high latitude convection electric fields.
Ben is always looking for new Ph.D. students from all backgrounds who are interested in data assimilation, statistics, machine learning, and space weather. At least some experience with programming is certainly an asset.
Interested students should send a complete CV, a brief (one page) summary of their research interests, and a link to their github page (if applicable).